As a key method to enhance the anti-jamming capability of Global Navigation Satellite System(GNSS),flex power technology enables ground-based commands to dynamically adjust satellite signals by redistributing signal c...As a key method to enhance the anti-jamming capability of Global Navigation Satellite System(GNSS),flex power technology enables ground-based commands to dynamically adjust satellite signals by redistributing signal components,thereby strengthening specific transmissions and improving service robustness in interference environments.Both the Global Positioning System(GPS)and the BeiDou Navigation Satellite System(BDS)support flex power functionality.Activating and deactivating of flex power can significantly impact the various aspects of GNSS performance and introduce new technical challenges.In this paper,we first analyze the flex power operational modes of GPS and BDS,then review existing detection methods to propose a novel detection approach applicable to both GPS and BDS.The proposed method employs carrier-to-noise density ratio(C/N0)and hardware delay as complementary indicators to achieve high detection accuracy with low false alarm rates.Subsequently,we investigate the impacts of flex power on cycle slip detection,code bias,satellite clock offset,phase bias,ionospheric corrections,and Precise Point Positioning(PPP).The results show that flex power affects several GNSS parameters with BDS exhibiting much greater sensitivity compared to GPS.To address these effects and advance resilient Positioning,Navigation,and Timing(PNT)theory,we propose the optimized estimation strategies for resilient code bias,satellite clock offset,and phase bias,along with an enhanced data processing framework for ionospheric modeling and PPP.The effectiveness of the proposed approaches is validated,demonstrating clear improvements in PNT service reliability.This study provides valuable insights and practical methodologies for enhancing the robustness of GNSS PNT services in flex power operations.展开更多
Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to en...Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.展开更多
During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h2/(4√2),where h is the piecewise length.展开更多
Mathematical programming solvers are software tools designed to solve real‑world problems using mathematical programming algorithms.This survey explores the evolution of optimization technologies,from traditional meth...Mathematical programming solvers are software tools designed to solve real‑world problems using mathematical programming algorithms.This survey explores the evolution of optimization technologies,from traditional methods such as the simplex algorithm and branch‑and‑bound techniques to modern advancements that are facilitated by parallel computing,GPU acceleration,and AI algorithms.We also emphasize the recent emergence of mathematical programming solvers developed by research institutes and companies headquartered in China as major players,who have achieved remarkable success in benchmarks when compared to established solvers.This article provides a comprehensive overview of the theoretical foundations,historical progress,and emerging trends in mathematical programming solvers,offering valuable insights for both researchers and practitioners in the field.展开更多
LEO satellite communication systems have the characteristics of high-speed and periodic movement.The handover of user link occurs frequently,which has a serious impact on user terminal application and system capacity....LEO satellite communication systems have the characteristics of high-speed and periodic movement.The handover of user link occurs frequently,which has a serious impact on user terminal application and system capacity.To address this issue,we propose a handover strategy of LEO satellite user terminal based on multi-attribute and multi-point(MAMP)cooperation.Firstly,the satellite-user-time matrix is established by using the satellite constellation coverage and handover model.Then,combined with the visual time and signal quality,the user access matrix and satellite load matrix are extracted to determine the weight equation of the handover strategy with the channel reservation.According to the system modeling simulation,the algorithm improves the handover success rate by 2.5%,the lasted call access success rate by 3.2%,the load balancing degree by 20%,and the robustness by two orders of magnitude.展开更多
Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disruptin...Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.展开更多
Satellite clock bias(SCB)prediction is essential for enhancing the accuracy and reliability of real-time precise point positioning(RT-PPP)in Global Navigation Satellite Systems(GNSS).To address the nonlinearity,non-st...Satellite clock bias(SCB)prediction is essential for enhancing the accuracy and reliability of real-time precise point positioning(RT-PPP)in Global Navigation Satellite Systems(GNSS).To address the nonlinearity,non-stationarity,and short-term interruptions of SCB data under complex environments,this paper proposes an enhanced SCB prediction model combining Temporal Convolutional Networks(TCN)and Transformers.Experimental results indicate that,in a 24-h prediction task,the proposed model reduces root mean square error(RMSE)and range error(RE)by 95.6%,86.0%,and 61.3%,and93.7%,86.3%,and 58.8%,respectively,compared with LSTM,Transformer,and CNN-BiGRU-Attention models,while improving computational efficiency by 48.6%over the Transformer.Moreover,although the clock bias products generated by the proposed method result in slightly higher static PPP positioning errors than the International GNSS Service(IGS)rapid clock products,the error differences are generally at the millimeter level,demonstrating the feasibility of using predicted clock bias products to replace rapid clock products in the short term.This method addresses the PPP positioning issue during short-term network service interruptions from the perspective of time series prediction and provides potential solutions for engineering applications such as landslide,earthquake,and subsidence monitoring.展开更多
Addressing climate change has become a global priority,and satellites play an important role.This study provides a bibliometric analysis and review of satellite-based climate change research from the perspectives of m...Addressing climate change has become a global priority,and satellites play an important role.This study provides a bibliometric analysis and review of satellite-based climate change research from the perspectives of mitigation and adaptation strategies from 1994 to 2025.The analysis reveals a shift from early emphases on climate change,atmospheric CO2,and remote sensing toward emerging topics involving vegetation,land use,air quality,variability,and land-cover dynamics.Existing satellite-based studies on climate change mitigation focus on identifying emission hotspots and quantifying CO2and CH4emissions from ecosystems and socioeconomic systems,while N2O and emissions from industrial processes and waste remain underexplored.Satellite-based climate change adaptation has been used to assess water resources,agricultural systems,forest cover,and sea level rise,yet challenges such as uneven water distribution,agricultural instability,forest degradation,and sea-level rise,as well as their impacts on ecosystems and biodiversity,remain insufficiently addressed.The study provides valuable future research directions for satellite-based climate change research.展开更多
In the conceptual design phase of the satellite thermal management system,components layout optimization and structural topology optimization of satellite panel can meet global and local thermal management requirement...In the conceptual design phase of the satellite thermal management system,components layout optimization and structural topology optimization of satellite panel can meet global and local thermal management requirements,respectively.However,achieving non-interfering coupling between these two optimization processes remains a challenge.An integrated layout-structure design method based on thermal metamaterials is proposed,which comprises two design stages.In the first stage,components layout optimization is conducted to maximize temperature uniformity within the satellite module,yielding a globally optimized layout with balanced thermal characteristics.In the second stage,topology optimization guided by the design principle of thermal metamaterials is implemented in critical local panel regions to satisfy differentiated heat transfer requirements of components with diverse functional and thermal sensitivity properties.The key innovation lies in utilizing thermal metamaterials as a mediator to synergistically couple global components layout optimization with local structural topology optimization,which enables customized local heat flux manipulation without interfering with the globally optimized temperature field derived from the layout optimization.The method introduces neither additional mass nor special materials,offering advantages of low cost,high reliability,and strong versatility.It provides a new solution paradigm for the design of passive thermal management systems in satellites.展开更多
As investigated by 3GPP,support of UPF(user plane function)onboard satellite can reduce the latency of communications via satellite,and then it becomes a key enhancement in 5G network integrating with satellite commun...As investigated by 3GPP,support of UPF(user plane function)onboard satellite can reduce the latency of communications via satellite,and then it becomes a key enhancement in 5G network integrating with satellite communication.However,current 5G system cannot support UPF onboard LEO(low earth orbit)satellites,as it would face challenges like UPF mobility handling,synchronization between mobile network and satellite network,and condition of activating local data switching.To solve such challenges,this paper proposes a solution to support UPF onboard LEO satellite,which consists of enhanced network architecture,I-UPF(intermediate UPF)based local data switching scheme and communication latency based data path selection.We subsequently develop analytic models for performance evaluation and conduct simulations using the constellation configuration of iridium II.The simulation results show that the data switching via I-UPF onboard LEO satellite can reduce E2E(end to end)packet delivery latency and E2E packet loss ratio significantly compared with that of routing the data back to 5GC on the ground.The proposed scheme yet has increased signaling cost for handling UPF mobility.els,compared with existing similar companding algorithms.展开更多
In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites t...In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites through detection can help solve three major scientific problems:the source of particles in the inner radiation belt,information on solar-accelerated particles,and the proportion of neutrons from different sources in near-Earth space.The detection efficiency and accuracy of neutrons are affected by charged and primary particles in the environment and secondary neutrons produced by the spacecraft itself,which has been a hot research topic.The neutron spectrometer developed in this study adopts two combinations of 15 silicon detectors in terms of detector type and arrangement,which are used for neutron detection via the nuclear reaction method and recoil proton method,respectively,in which a 27μm-thick6LiF conversion layer is used for thermal neutron detection up to 0.4 eV and a 300μm-thick high-density polyethylene conversion layer is used for fast-neutron detection up to 14 MeV and below.The design of the detector set can also remove the influence of primary charged particles and secondary neutrons in the detection environment to a certain extent,thereby improving the accuracy of neutron detection.In this study,the neutron spectrometer hardware,firmware,software design,and basic performance of the front-end readout chip SKIROC2A were tested.The readout circuit of each channel baseline ADC code was less than 17;thus,the channel consistency was good.The RMS noise of the channel baseline was only 7.1 mV and exhibited good stability.The maximum number of events that could be processed per second is 75.The overall power consumption was 3 W,the weight was 792 g,and the volume was less than 1 dm3.Furthermore,the neutron spectrometer was tested for principle and detection efficiency using various neutron sources,such as 241Am-Be neutron source,2.5 MeV neutron beam,and 14 MeV neutron beam,and the experiments were analyzed with corresponding simulations.The experimental data and simulation results were in good agreement and met the design requirements.The intrinsic detection efficiency of the probes used in the neutron spectrometer was 1.05%for 14 MeV fast neutrons.展开更多
It is important for a lunar lander to possess a large divert capability during the final landing phase,as this can enhance the tolerance for flight deviations in the early phase or improve the obstacle avoidance perfo...It is important for a lunar lander to possess a large divert capability during the final landing phase,as this can enhance the tolerance for flight deviations in the early phase or improve the obstacle avoidance performance.Therefore,when designing the powered descent trajectory,sufficient final phase divert capability should be reserved at the minimum propellant cost.To this end,a multi-phase trajectory programming(MPTP)method for powered descent with approaching phase divert capability is proposed.First,the entire powered descent trajectory is divided into the main braking phase and the approaching phase.The main braking phase is responsible for dissipating the majority of the initial velocity.The approaching phase is responsible for safely and precisely flying toward the landing site.It is nominally a vertical descent trajectory and possesses equal divert capability in all horizontal directions.Then,a constant-thrust linear tangent guidance(LTG)accounting for the lunar curvature is designed for the main braking phase.For the approaching phase,a variable-thrust lossless convex programming(LCP)guidance considering the constraints of tilt angle and glide-slope angle is developed.Subsequently,to connect the two phases and further optimize the propellant consumption throughout the entire trajectory,a method for determining the phase switching condition is proposed.The originally difficult-to-solve two-parameter optimization problem is decomposed into two more easily solvable subproblems,which are solved iteratively via a bilevel optimization framework.Finally,the divert capability of the proposed method is verified through numerical simulation.The programmed trajectory is basically consistent with the results of the pseudospectral method,with the difference in propellant consumption being only 0.006%.This method is suitable for the rapid iterative design of nominal trajectories for lunar lander powered descent in engineering applications.展开更多
Amplitude Phase Shift Keying(APSK)is more suitable for the nonlinear channels of Low Earth Orbit(LEO)satellite communication systems compared to Quadrature Amplitude Modulation(QAM).To tackle challenges posed by Direc...Amplitude Phase Shift Keying(APSK)is more suitable for the nonlinear channels of Low Earth Orbit(LEO)satellite communication systems compared to Quadrature Amplitude Modulation(QAM).To tackle challenges posed by Direct Current(DC)interference and high demodulation complexity,we propose an APSK demodulation algorithm based on K-means clustering.Initially,static DC components are calculated and removed from the received APSK signals.Subsequently,the estimated APSK constellation points serve as initial centers for K-means clustering.These centers are refined through the K-means process and act as theoretical APSK constellation points for the Max-Log-MAP demodulation algorithm,effectively eliminating residual DC.We then introduce a low-complexity APSK demodulation algorithm that utilizes the symmetry of constellation points along with the Euclidean distance between DC-eliminated signals and these constellation points to minimize the set of constellation points.Simulation results indicate that for 32-APSK,our proposed demodulation submodule reduces computational complexity to approximately one-third that of the Max-Log-MAP algorithm while improving Bit Error Rate(BER)performance by about 0.23 dB.Furthermore,end-to-end simulation experiments conducted within LEO satellite communication systems demonstrate that our approach not only maintains this complexity advantage but also enhances BER performance by approximately 1.1 dB.展开更多
The Agile Earth Observation Satellite Scheduling Problem(AEOSSP)is a complex NP‑hard challenge that involves selecting,sequencing,and timing observation tasks to maximize imaging profits while adhering to various cons...The Agile Earth Observation Satellite Scheduling Problem(AEOSSP)is a complex NP‑hard challenge that involves selecting,sequencing,and timing observation tasks to maximize imaging profits while adhering to various constraints.In our study,we developed a mixed‑integer programming model for AEOSSP,incorporating key constraints related to visible time windows and time dependencies.To tackle this,we propose an Evolutionary Adaptive Large Neighborhood Search Algorithm(evALNS)enhanced by Large Language Models(LLMs).Our work pioneers the application of LLMs to ALNS by being the first to automatically develop and evolve its critical destroy heuristics.However,a naive application of LLMs is insufficient for such a complex domain.We therefore introduce a novel Dual‑Population Co‑Evolutionary Computing Framework(DPEC)to bridge the LLM’s knowledge gap by synergizing LLM‑generated heuristics with expert‑designed ones.This co‑evolution,guided by a Functional Natural Language Embedding(FNLE)strategy and customized prompts,significantly enhances the adaptability and efficiency of ALNS.Extensive numerical experiments demonstrated the superiority of the evALNS evolved under our framework,achieving an average profit improvement of 8.48%compared to the original ALNS with expert‑designed destroy operators.展开更多
The Global Positioning System(GPS)satellite constellation has provided long-term observations of energetic elec trons in Earth’s radiation belts,but inconsistencies among different satellites limit the direct use of ...The Global Positioning System(GPS)satellite constellation has provided long-term observations of energetic elec trons in Earth’s radiation belts,but inconsistencies among different satellites limit the direct use of their combined measurements.A comparative analysis of electron flux data from year 2000 to 2020 reveals significant deviations for several satellites,particularly NS41 and NS48 in low-flux regions,as well as scattered observations from satellites such as NS74 and NS69.These discrepancies highlight the necessity of cross-calibration to ensure data consistency.To address this,we conducted the first systematic cross-calibration of energetic electron fluxes from 25 GPS satel lites.Taking the 2.0 MeV average unidirectional differential electron fluxes and the≥2.0 MeV omnidirectional integral electron fluxes as examples,we adopted the conjunction method in magnetic coordinates(Lm,B/B0)(Lm:McIlwain L-shell parameter,B/B0:magnetic field ratio)and applied cubic polynomial fitting to achieve unified calibration using NS59 as the reference.For the 2.0 MeV differential electron fluxes,the Root-Mean-Square Deviation(RMSD)before cal ibration is on average 3.08 times larger than that after calibration,while the Correlation Coefficient(CC)increases by a factor of 1.14 on average.For the≥2.0 MeV integral electron fluxes,the corresponding values are 1.68 and 1.01,respectively.This method can be extended to other energy channels and satellites.The calibrated dataset facilitates quantitative analysis and modeling of variations in the high-energy electron distribution in medium Earth orbits.展开更多
This paper delves into the H∞optimal output regulation problem for continuous-time linear systems with an unknown system model.By integrating the internal model principle with optimal control,we derive an optimal con...This paper delves into the H∞optimal output regulation problem for continuous-time linear systems with an unknown system model.By integrating the internal model principle with optimal control,we derive an optimal control policy and a worst-case disturbance policy through the formulation and solution of a zero-sum game problem.Subsequently,leveraging adaptive dynamic programming,we propose a policy iteration learning algorithm capable of learning both the optimal control policy and the worst-case disturbance policy directly from system data.The existing algorithms necessitate an initial stabilizing policy,a full-rank condition,and the storage of historical data to guarantee algorithm convergence.In contrast,we design a dual policy iteration algorithm equipped with an online learning mechanism,thereby eliminating these additional prerequisites.Simulation results with an antonomous ground vehicle underscore the effectiveness of our proposed algorithm,and its superiority is further demonstrated through comparisons with existing methodologies.展开更多
Low earth orbit(LEO)satellite networks are entering a critical phase of large-scale global deployment.However,their high dynamics pose unprecedented challenges to traditional terrestrial mobile communication and netwo...Low earth orbit(LEO)satellite networks are entering a critical phase of large-scale global deployment.However,their high dynamics pose unprecedented challenges to traditional terrestrial mobile communication and networking protocols.Although artificial intelligence(AI)technology provides new solution paths for high-efficiency and low-complexity operations,it still faces severe technical bottlenecks in practical application and deployment.This paper systematically analyzes three key challenges during the intelligent evolution of LEO satellites:model generalization issue,constrained payload capabilities,and decision latency bottleneck.In response to these challenges,this paper explores potential enabling AI technologies,including the use of meta-learning and graph neural networks to enhance model generalization,the implementation of model compression and lightweight strategies,and the application of generative AI and delay-tolerant reinforcement learning to improve resource management efficiency and decision robustness.On this basis,a further outlook on typical AI-enabled application scenarios is provided:at the communication transmission level,the paper highlights generative AI-driven channel estimation,delay-tolerant beam management,and interference suppression techniques based on diffusion models;at the networking level,graph-based routing strategies and meta-learning-based handover management schemes are discussed.The deep integration of AI technology and satellite communication regimes will serve as a critical support for constructing autonomous and ubiquitously intelligent integrated space information systems in the 6G era.展开更多
With the development of Sixth-Generation(6G)mobile communication technologies,Low Earth Orbit(LEO)satellite communication systems have become extremely important in mobile communications owing to their large coverage,...With the development of Sixth-Generation(6G)mobile communication technologies,Low Earth Orbit(LEO)satellite communication systems have become extremely important in mobile communications owing to their large coverage,high efficiency,and low cost.However,the high dynamic LEO satellite channels cause serious time-frequency dual selective fading,significantly impairing the performance of conventional single time or frequency domain synchronization algorithms and limiting their applicability.To address these challenges,this paper proposes a synchronization algorithm based on Linear Frequency Modulation(LFM)signals and the Fractional Fourier Transform(FRFT).Exploiting the inherent robustness of LFM signals against frequency deviations and multipath effects,coupled with their energy concentration property in the optimal fractional Fourier domain,the proposed algorithm enables efficient synchronization with enhanced resilience to time-frequency variations.Furthermore,LFM preamble sequences are optimally designed for diverse channel conditions.This work presents a theoretical analysis of the time-frequency nonstationary characteristics of LEO satellite channels and discusses the performance limitations of traditional synchronization algorithms.The proposed integrated FRFTLFM synchronization framework and sequence optimization scheme are rigorously evaluated via comprehensive simulations.The results demonstrate substantial improvements in synchronization accuracy and computational efficiency compared with conventional methods,particularly under time-frequency dual selective fading LEO satellite channels.The algorithm provides a robust and reliable solution for time-frequency synchronization in LEO satellite communication systems,thereby enhancing overall system performance and reliability.展开更多
The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary sate...The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary satellites are not timevarying,a primary source of inaccuracy in solar positioning is the use of a single timestamp.Since pixel scanning times can differ significantly across the field-of-view disk(e.g.,by approximately 13 min for Fengyun-4B),this practice leads to errors of up to±2°in solar zenith angle,which translates to±50 W m−2 in extraterrestrial irradiance;the errors in solar azimuth angle can exceed±100°.Beyond scanning time,this work also quantifies the impact of other inputs—including altitude,surface pressure,air temperature,difference between Terrestrial Time and Universal Time,and atmospheric refraction—on the resulting angles.A comparison of our precise calculations with the official National Satellite Meteorological Center L1_GEO product shows an accuracy within 0.1°,confirming its utility for most retrieval tasks.To facilitate higher precision when required,this work releases the corresponding satellite and solar positioning codes in both R and Python.展开更多
The operational demands of a wide range significantly exacerbate combustion instability issues within ramjet combustor.To suppress combustion oscillations,an open-loop control system utilizing Linear Genetic Programmi...The operational demands of a wide range significantly exacerbate combustion instability issues within ramjet combustor.To suppress combustion oscillations,an open-loop control system utilizing Linear Genetic Programming(LGP)has been developed for a full-scale annular ramjet combustor.The LGP is used to generate control laws that include multi-frequency forcing.These laws are then transformed into square waves to actuate the solenoid valve,which modulates the kerosene supply for open-loop control.The results show that the duty cycle has little effect on instability amplitude,whereas an increase in frequency leads to a remarked reduction in combustion amplitude.After five generations evolvements,the pressure amplitude is reduced by 40.6% under the optimal control law generated by LGP.Furthermore,the machine learning process is depicted using a proximity map of control law similarity,with the search pathway visualized by the steepest descent.All individuals go forward to the upper left corner of the map with the evolution process,terminating at the optimal individual of the fifth generation.展开更多
基金funded by Scientific Research Key Laboratory Fund(Grant No.SYS-ZX02-2024-01).
摘要As a key method to enhance the anti-jamming capability of Global Navigation Satellite System(GNSS),flex power technology enables ground-based commands to dynamically adjust satellite signals by redistributing signal components,thereby strengthening specific transmissions and improving service robustness in interference environments.Both the Global Positioning System(GPS)and the BeiDou Navigation Satellite System(BDS)support flex power functionality.Activating and deactivating of flex power can significantly impact the various aspects of GNSS performance and introduce new technical challenges.In this paper,we first analyze the flex power operational modes of GPS and BDS,then review existing detection methods to propose a novel detection approach applicable to both GPS and BDS.The proposed method employs carrier-to-noise density ratio(C/N0)and hardware delay as complementary indicators to achieve high detection accuracy with low false alarm rates.Subsequently,we investigate the impacts of flex power on cycle slip detection,code bias,satellite clock offset,phase bias,ionospheric corrections,and Precise Point Positioning(PPP).The results show that flex power affects several GNSS parameters with BDS exhibiting much greater sensitivity compared to GPS.To address these effects and advance resilient Positioning,Navigation,and Timing(PNT)theory,we propose the optimized estimation strategies for resilient code bias,satellite clock offset,and phase bias,along with an enhanced data processing framework for ionospheric modeling and PPP.The effectiveness of the proposed approaches is validated,demonstrating clear improvements in PNT service reliability.This study provides valuable insights and practical methodologies for enhancing the robustness of GNSS PNT services in flex power operations.
基金supported by the National Natural Science Foundation of China(No.92371206)the Postgraduate Scientific Research Innovation Project of Hunan Province,China(No.CX2023063).
摘要Satellite Component Layout Optimization(SCLO) is crucial in satellite system design.This paper proposes a novel Satellite Three-Dimensional Component Assignment and Layout Optimization(3D-SCALO) problem tailored to engineering requirements, aiming to optimize satellite heat dissipation while considering constraints on static stability, 3D geometric relationships between components, and special component positions. The 3D-SCALO problem is a challenging bilevel combinatorial optimization task, involving the optimization of discrete component assignment variables in the outer layer and continuous component position variables in the inner layer,with both influencing each other. To address this issue, first, a Mixed Integer Programming(MIP) model is proposed, which reformulates the original bilevel problem into a single-level optimization problem, enabling the exploration of a more comprehensive optimization space while avoiding iterative nested optimization. Then, to model the 3D geometric relationships between components within the MIP framework, a linearized 3D Phi-function method is proposed, which handles non-overlapping and safety distance constraints between cuboid components in an explicit and effective way. Subsequently, the Finite-Rectangle Method(FRM) is proposed to manage 3D geometric constraints for complex-shaped components by approximating them with a finite set of cuboids, extending the applicability of the geometric modeling approach. Finally, the feasibility and effectiveness of the proposed MIP model are demonstrated through two numerical examples"and a real-world engineering case, which confirms its suitability for complex-shaped components and real engineering applications.
基金supported by the National Natural Sci‐ence Foundation of China(Grant No.62306325)。
摘要During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h2/(4√2),where h is the piecewise length.
基金supported by the National Natural Science Foundation of China(Grant Nos.72425001,72401219,72231006,and 72301165).
摘要Mathematical programming solvers are software tools designed to solve real‑world problems using mathematical programming algorithms.This survey explores the evolution of optimization technologies,from traditional methods such as the simplex algorithm and branch‑and‑bound techniques to modern advancements that are facilitated by parallel computing,GPU acceleration,and AI algorithms.We also emphasize the recent emergence of mathematical programming solvers developed by research institutes and companies headquartered in China as major players,who have achieved remarkable success in benchmarks when compared to established solvers.This article provides a comprehensive overview of the theoretical foundations,historical progress,and emerging trends in mathematical programming solvers,offering valuable insights for both researchers and practitioners in the field.
基金supported by the Innovation Funding of ICT,CAS under Grant(No.E261020)Jiangsu Key Research and Development Program of China(No.BE2021013-2)Zhejiang Key Research and Development Program(No.2021C01040).
摘要LEO satellite communication systems have the characteristics of high-speed and periodic movement.The handover of user link occurs frequently,which has a serious impact on user terminal application and system capacity.To address this issue,we propose a handover strategy of LEO satellite user terminal based on multi-attribute and multi-point(MAMP)cooperation.Firstly,the satellite-user-time matrix is established by using the satellite constellation coverage and handover model.Then,combined with the visual time and signal quality,the user access matrix and satellite load matrix are extracted to determine the weight equation of the handover strategy with the channel reservation.According to the system modeling simulation,the algorithm improves the handover success rate by 2.5%,the lasted call access success rate by 3.2%,the load balancing degree by 20%,and the robustness by two orders of magnitude.
基金financially supported by Ministerio de Ciencia e Innovación projects SAF2017-82736-C2-1-R to MTMFin Universidad Autónoma de Madrid and by Fundación Universidad Francisco de Vitoria to JS+2 种基金a predoctoral scholarship from Fundación Universidad Francisco de Vitoriafinancial support from a 6-month contract from Universidad Autónoma de Madrida 3-month contract from the School of Medicine of Universidad Francisco de Vitoria。
摘要Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.
基金supported by the National Natural Science Foundation of China(42304050)Major Science and Technology Projects in Anhui Province,grant number(202103a05020026)+1 种基金Open Foundation of the Key Laboratory of Universities in Anhui Province for Prevention of Mine Geological Disasters(2022-MGDP-08)University Natural Science Research Project of Anhui Province(2023AH051190)。
摘要Satellite clock bias(SCB)prediction is essential for enhancing the accuracy and reliability of real-time precise point positioning(RT-PPP)in Global Navigation Satellite Systems(GNSS).To address the nonlinearity,non-stationarity,and short-term interruptions of SCB data under complex environments,this paper proposes an enhanced SCB prediction model combining Temporal Convolutional Networks(TCN)and Transformers.Experimental results indicate that,in a 24-h prediction task,the proposed model reduces root mean square error(RMSE)and range error(RE)by 95.6%,86.0%,and 61.3%,and93.7%,86.3%,and 58.8%,respectively,compared with LSTM,Transformer,and CNN-BiGRU-Attention models,while improving computational efficiency by 48.6%over the Transformer.Moreover,although the clock bias products generated by the proposed method result in slightly higher static PPP positioning errors than the International GNSS Service(IGS)rapid clock products,the error differences are generally at the millimeter level,demonstrating the feasibility of using predicted clock bias products to replace rapid clock products in the short term.This method addresses the PPP positioning issue during short-term network service interruptions from the perspective of time series prediction and provides potential solutions for engineering applications such as landslide,earthquake,and subsidence monitoring.
基金supported by National Natural Science Foundation of China(Grant Nos.91538113,72071195,and 71402176)Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2019171)MOE Social Sciences Innovative Group on Complex Systems Modeling in Economic Management in the Era of Digital Intelligence,University of Chinese Academy of Sciences.
摘要Addressing climate change has become a global priority,and satellites play an important role.This study provides a bibliometric analysis and review of satellite-based climate change research from the perspectives of mitigation and adaptation strategies from 1994 to 2025.The analysis reveals a shift from early emphases on climate change,atmospheric CO2,and remote sensing toward emerging topics involving vegetation,land use,air quality,variability,and land-cover dynamics.Existing satellite-based studies on climate change mitigation focus on identifying emission hotspots and quantifying CO2and CH4emissions from ecosystems and socioeconomic systems,while N2O and emissions from industrial processes and waste remain underexplored.Satellite-based climate change adaptation has been used to assess water resources,agricultural systems,forest cover,and sea level rise,yet challenges such as uneven water distribution,agricultural instability,forest degradation,and sea-level rise,as well as their impacts on ecosystems and biodiversity,remain insufficiently addressed.The study provides valuable future research directions for satellite-based climate change research.
基金funded by State Key Laboratory of MicroSpacecraft Rapid Design and Intelligent Cluster,China(No.MS01240104)the Youth Program of the Self-Innovation Science Fund,China(No.ZK2023-41)from the National University of Defense Technology(NUDT)China and the Postgraduate Scientific Research Innovation Project of Hunan Province,China(No.CX20240155)。
摘要In the conceptual design phase of the satellite thermal management system,components layout optimization and structural topology optimization of satellite panel can meet global and local thermal management requirements,respectively.However,achieving non-interfering coupling between these two optimization processes remains a challenge.An integrated layout-structure design method based on thermal metamaterials is proposed,which comprises two design stages.In the first stage,components layout optimization is conducted to maximize temperature uniformity within the satellite module,yielding a globally optimized layout with balanced thermal characteristics.In the second stage,topology optimization guided by the design principle of thermal metamaterials is implemented in critical local panel regions to satisfy differentiated heat transfer requirements of components with diverse functional and thermal sensitivity properties.The key innovation lies in utilizing thermal metamaterials as a mediator to synergistically couple global components layout optimization with local structural topology optimization,which enables customized local heat flux manipulation without interfering with the globally optimized temperature field derived from the layout optimization.The method introduces neither additional mass nor special materials,offering advantages of low cost,high reliability,and strong versatility.It provides a new solution paradigm for the design of passive thermal management systems in satellites.
基金supported by the national key research and development program of China under Grant 2020YFB1807901the National Science Foundation Project in China under grant 61931005.
摘要As investigated by 3GPP,support of UPF(user plane function)onboard satellite can reduce the latency of communications via satellite,and then it becomes a key enhancement in 5G network integrating with satellite communication.However,current 5G system cannot support UPF onboard LEO(low earth orbit)satellites,as it would face challenges like UPF mobility handling,synchronization between mobile network and satellite network,and condition of activating local data switching.To solve such challenges,this paper proposes a solution to support UPF onboard LEO satellite,which consists of enhanced network architecture,I-UPF(intermediate UPF)based local data switching scheme and communication latency based data path selection.We subsequently develop analytic models for performance evaluation and conduct simulations using the constellation configuration of iridium II.The simulation results show that the data switching via I-UPF onboard LEO satellite can reduce E2E(end to end)packet delivery latency and E2E packet loss ratio significantly compared with that of routing the data back to 5GC on the ground.The proposed scheme yet has increased signaling cost for handling UPF mobility.els,compared with existing similar companding algorithms.
基金supported by the National Natural Science Foundation of China(NSFC)(Nos.42225405 and U2106202)。
摘要In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites through detection can help solve three major scientific problems:the source of particles in the inner radiation belt,information on solar-accelerated particles,and the proportion of neutrons from different sources in near-Earth space.The detection efficiency and accuracy of neutrons are affected by charged and primary particles in the environment and secondary neutrons produced by the spacecraft itself,which has been a hot research topic.The neutron spectrometer developed in this study adopts two combinations of 15 silicon detectors in terms of detector type and arrangement,which are used for neutron detection via the nuclear reaction method and recoil proton method,respectively,in which a 27μm-thick6LiF conversion layer is used for thermal neutron detection up to 0.4 eV and a 300μm-thick high-density polyethylene conversion layer is used for fast-neutron detection up to 14 MeV and below.The design of the detector set can also remove the influence of primary charged particles and secondary neutrons in the detection environment to a certain extent,thereby improving the accuracy of neutron detection.In this study,the neutron spectrometer hardware,firmware,software design,and basic performance of the front-end readout chip SKIROC2A were tested.The readout circuit of each channel baseline ADC code was less than 17;thus,the channel consistency was good.The RMS noise of the channel baseline was only 7.1 mV and exhibited good stability.The maximum number of events that could be processed per second is 75.The overall power consumption was 3 W,the weight was 792 g,and the volume was less than 1 dm3.Furthermore,the neutron spectrometer was tested for principle and detection efficiency using various neutron sources,such as 241Am-Be neutron source,2.5 MeV neutron beam,and 14 MeV neutron beam,and the experiments were analyzed with corresponding simulations.The experimental data and simulation results were in good agreement and met the design requirements.The intrinsic detection efficiency of the probes used in the neutron spectrometer was 1.05%for 14 MeV fast neutrons.
基金Fourth Phase of the China's Lunar Exploration ProgramChina National Space Administration (D040103)+1 种基金National Natural Science Foundation of China (62394354)National Key Research and Development Program of China (2025YFF0513303).
摘要It is important for a lunar lander to possess a large divert capability during the final landing phase,as this can enhance the tolerance for flight deviations in the early phase or improve the obstacle avoidance performance.Therefore,when designing the powered descent trajectory,sufficient final phase divert capability should be reserved at the minimum propellant cost.To this end,a multi-phase trajectory programming(MPTP)method for powered descent with approaching phase divert capability is proposed.First,the entire powered descent trajectory is divided into the main braking phase and the approaching phase.The main braking phase is responsible for dissipating the majority of the initial velocity.The approaching phase is responsible for safely and precisely flying toward the landing site.It is nominally a vertical descent trajectory and possesses equal divert capability in all horizontal directions.Then,a constant-thrust linear tangent guidance(LTG)accounting for the lunar curvature is designed for the main braking phase.For the approaching phase,a variable-thrust lossless convex programming(LCP)guidance considering the constraints of tilt angle and glide-slope angle is developed.Subsequently,to connect the two phases and further optimize the propellant consumption throughout the entire trajectory,a method for determining the phase switching condition is proposed.The originally difficult-to-solve two-parameter optimization problem is decomposed into two more easily solvable subproblems,which are solved iteratively via a bilevel optimization framework.Finally,the divert capability of the proposed method is verified through numerical simulation.The programmed trajectory is basically consistent with the results of the pseudospectral method,with the difference in propellant consumption being only 0.006%.This method is suitable for the rapid iterative design of nominal trajectories for lunar lander powered descent in engineering applications.
基金the Key Project of the Chongqing Natural Science Foundation(2022NSCQ-LZX0191)the Key Research Program of Science and Technology of the Chongqing Education Commission(KJZD-K202202402)+1 种基金the Scientific Research Start-up Fund of Chongqing University of Posts and Telecommunications(A2023-62)the Chongqing Natural Science Foundation(cstc2024ycjh-bgzxm003)for their invaluable support in this research。
摘要Amplitude Phase Shift Keying(APSK)is more suitable for the nonlinear channels of Low Earth Orbit(LEO)satellite communication systems compared to Quadrature Amplitude Modulation(QAM).To tackle challenges posed by Direct Current(DC)interference and high demodulation complexity,we propose an APSK demodulation algorithm based on K-means clustering.Initially,static DC components are calculated and removed from the received APSK signals.Subsequently,the estimated APSK constellation points serve as initial centers for K-means clustering.These centers are refined through the K-means process and act as theoretical APSK constellation points for the Max-Log-MAP demodulation algorithm,effectively eliminating residual DC.We then introduce a low-complexity APSK demodulation algorithm that utilizes the symmetry of constellation points along with the Euclidean distance between DC-eliminated signals and these constellation points to minimize the set of constellation points.Simulation results indicate that for 32-APSK,our proposed demodulation submodule reduces computational complexity to approximately one-third that of the Max-Log-MAP algorithm while improving Bit Error Rate(BER)performance by about 0.23 dB.Furthermore,end-to-end simulation experiments conducted within LEO satellite communication systems demonstrate that our approach not only maintains this complexity advantage but also enhances BER performance by approximately 1.1 dB.
基金supported by the National Natural Science Foundation of China(Grant No.72201272 and 72501042)the Young Elite Scientists Sponsorship Program by CAST(Grant No.2023‑JCIQ‑QT‑042)The Science and Technology Innovation Program of Hunan Province(Grant No.2025RC3111).
摘要The Agile Earth Observation Satellite Scheduling Problem(AEOSSP)is a complex NP‑hard challenge that involves selecting,sequencing,and timing observation tasks to maximize imaging profits while adhering to various constraints.In our study,we developed a mixed‑integer programming model for AEOSSP,incorporating key constraints related to visible time windows and time dependencies.To tackle this,we propose an Evolutionary Adaptive Large Neighborhood Search Algorithm(evALNS)enhanced by Large Language Models(LLMs).Our work pioneers the application of LLMs to ALNS by being the first to automatically develop and evolve its critical destroy heuristics.However,a naive application of LLMs is insufficient for such a complex domain.We therefore introduce a novel Dual‑Population Co‑Evolutionary Computing Framework(DPEC)to bridge the LLM’s knowledge gap by synergizing LLM‑generated heuristics with expert‑designed ones.This co‑evolution,guided by a Functional Natural Language Embedding(FNLE)strategy and customized prompts,significantly enhances the adaptability and efficiency of ALNS.Extensive numerical experiments demonstrated the superiority of the evALNS evolved under our framework,achieving an average profit improvement of 8.48%compared to the original ALNS with expert‑designed destroy operators.
基金funded by the China Postdoctoral Science Foundation 2025M784268the National Natural Science Foundation of China Grants 42441809+1 种基金the National Natural Science Foundation of China Project U2106201the NSFC Regional Innovation and Development Joint Fund U25A20784.
摘要The Global Positioning System(GPS)satellite constellation has provided long-term observations of energetic elec trons in Earth’s radiation belts,but inconsistencies among different satellites limit the direct use of their combined measurements.A comparative analysis of electron flux data from year 2000 to 2020 reveals significant deviations for several satellites,particularly NS41 and NS48 in low-flux regions,as well as scattered observations from satellites such as NS74 and NS69.These discrepancies highlight the necessity of cross-calibration to ensure data consistency.To address this,we conducted the first systematic cross-calibration of energetic electron fluxes from 25 GPS satel lites.Taking the 2.0 MeV average unidirectional differential electron fluxes and the≥2.0 MeV omnidirectional integral electron fluxes as examples,we adopted the conjunction method in magnetic coordinates(Lm,B/B0)(Lm:McIlwain L-shell parameter,B/B0:magnetic field ratio)and applied cubic polynomial fitting to achieve unified calibration using NS59 as the reference.For the 2.0 MeV differential electron fluxes,the Root-Mean-Square Deviation(RMSD)before cal ibration is on average 3.08 times larger than that after calibration,while the Correlation Coefficient(CC)increases by a factor of 1.14 on average.For the≥2.0 MeV integral electron fluxes,the corresponding values are 1.68 and 1.01,respectively.This method can be extended to other energy channels and satellites.The calibrated dataset facilitates quantitative analysis and modeling of variations in the high-energy electron distribution in medium Earth orbits.
基金supported by the National Natural Science Foundation of China(62322305,62495090,62495095)。
摘要This paper delves into the H∞optimal output regulation problem for continuous-time linear systems with an unknown system model.By integrating the internal model principle with optimal control,we derive an optimal control policy and a worst-case disturbance policy through the formulation and solution of a zero-sum game problem.Subsequently,leveraging adaptive dynamic programming,we propose a policy iteration learning algorithm capable of learning both the optimal control policy and the worst-case disturbance policy directly from system data.The existing algorithms necessitate an initial stabilizing policy,a full-rank condition,and the storage of historical data to guarantee algorithm convergence.In contrast,we design a dual policy iteration algorithm equipped with an online learning mechanism,thereby eliminating these additional prerequisites.Simulation results with an antonomous ground vehicle underscore the effectiveness of our proposed algorithm,and its superiority is further demonstrated through comparisons with existing methodologies.
基金supported by the National Science and Technology Major Project of China under Grant 2026ZD1307000the National Natural Science Foundation of China under Grant 62371067.
摘要Low earth orbit(LEO)satellite networks are entering a critical phase of large-scale global deployment.However,their high dynamics pose unprecedented challenges to traditional terrestrial mobile communication and networking protocols.Although artificial intelligence(AI)technology provides new solution paths for high-efficiency and low-complexity operations,it still faces severe technical bottlenecks in practical application and deployment.This paper systematically analyzes three key challenges during the intelligent evolution of LEO satellites:model generalization issue,constrained payload capabilities,and decision latency bottleneck.In response to these challenges,this paper explores potential enabling AI technologies,including the use of meta-learning and graph neural networks to enhance model generalization,the implementation of model compression and lightweight strategies,and the application of generative AI and delay-tolerant reinforcement learning to improve resource management efficiency and decision robustness.On this basis,a further outlook on typical AI-enabled application scenarios is provided:at the communication transmission level,the paper highlights generative AI-driven channel estimation,delay-tolerant beam management,and interference suppression techniques based on diffusion models;at the networking level,graph-based routing strategies and meta-learning-based handover management schemes are discussed.The deep integration of AI technology and satellite communication regimes will serve as a critical support for constructing autonomous and ubiquitously intelligent integrated space information systems in the 6G era.
基金supported by the Beijing Natural Science Foundation(4252008)the Natural Science Foundation of Chongqing Province(CSTB2024NSCQLZX0176)the Beijing Natural Science Foundation of Undergraduate Qiyan Program(QY24197)。
摘要With the development of Sixth-Generation(6G)mobile communication technologies,Low Earth Orbit(LEO)satellite communication systems have become extremely important in mobile communications owing to their large coverage,high efficiency,and low cost.However,the high dynamic LEO satellite channels cause serious time-frequency dual selective fading,significantly impairing the performance of conventional single time or frequency domain synchronization algorithms and limiting their applicability.To address these challenges,this paper proposes a synchronization algorithm based on Linear Frequency Modulation(LFM)signals and the Fractional Fourier Transform(FRFT).Exploiting the inherent robustness of LFM signals against frequency deviations and multipath effects,coupled with their energy concentration property in the optimal fractional Fourier domain,the proposed algorithm enables efficient synchronization with enhanced resilience to time-frequency variations.Furthermore,LFM preamble sequences are optimally designed for diverse channel conditions.This work presents a theoretical analysis of the time-frequency nonstationary characteristics of LEO satellite channels and discusses the performance limitations of traditional synchronization algorithms.The proposed integrated FRFTLFM synchronization framework and sequence optimization scheme are rigorously evaluated via comprehensive simulations.The results demonstrate substantial improvements in synchronization accuracy and computational efficiency compared with conventional methods,particularly under time-frequency dual selective fading LEO satellite channels.The algorithm provides a robust and reliable solution for time-frequency synchronization in LEO satellite communication systems,thereby enhancing overall system performance and reliability.
基金supported by the National Natural Science Foundation of China(Grant No.42375192).
摘要The calculation of viewing and solar geometry angles is a critical first step in retrieving atmospheric and surface variables from geostationary satellite observations.Whereas the viewing angles for geostationary satellites are not timevarying,a primary source of inaccuracy in solar positioning is the use of a single timestamp.Since pixel scanning times can differ significantly across the field-of-view disk(e.g.,by approximately 13 min for Fengyun-4B),this practice leads to errors of up to±2°in solar zenith angle,which translates to±50 W m−2 in extraterrestrial irradiance;the errors in solar azimuth angle can exceed±100°.Beyond scanning time,this work also quantifies the impact of other inputs—including altitude,surface pressure,air temperature,difference between Terrestrial Time and Universal Time,and atmospheric refraction—on the resulting angles.A comparison of our precise calculations with the official National Satellite Meteorological Center L1_GEO product shows an accuracy within 0.1°,confirming its utility for most retrieval tasks.To facilitate higher precision when required,this work releases the corresponding satellite and solar positioning codes in both R and Python.
基金support from the National Natural Science Foundation of China(No.12002372)the Young Elite Scientists Sponsorship Program by China Association for Science and Technology(No.2022QNRC001)the Natural Science Foundation of Hunan Province,China(No.2021JJ40674)。
摘要The operational demands of a wide range significantly exacerbate combustion instability issues within ramjet combustor.To suppress combustion oscillations,an open-loop control system utilizing Linear Genetic Programming(LGP)has been developed for a full-scale annular ramjet combustor.The LGP is used to generate control laws that include multi-frequency forcing.These laws are then transformed into square waves to actuate the solenoid valve,which modulates the kerosene supply for open-loop control.The results show that the duty cycle has little effect on instability amplitude,whereas an increase in frequency leads to a remarked reduction in combustion amplitude.After five generations evolvements,the pressure amplitude is reduced by 40.6% under the optimal control law generated by LGP.Furthermore,the machine learning process is depicted using a proximity map of control law similarity,with the search pathway visualized by the steepest descent.All individuals go forward to the upper left corner of the map with the evolution process,terminating at the optimal individual of the fifth generation.