A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and...A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and magnetometer are introduced to construct an error equation with the gyros,thus the drifting characteristics of gyroscope can be compensated by solving the error equation utilized by the gradient descent algorithm.Performance of the presented algorithm is evaluated using a self-proposed micro-electro-mechanical system(MEMS)based attitude heading reference system which is mounted on a tri-axis turntable.The on-ground,turntable and flight experiments indicate that the estimation attitude has a good accuracy.Also,the presented system is compared with an open-source flight control system which runs extended Kalman filter(EKF),and the results show that the attitude control system using the gradient descent method can estimate the attitudes for UAV effectively.展开更多
The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks,which is an optimization algorithm for finding a local minimum of an objective function.The quantum vers...The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks,which is an optimization algorithm for finding a local minimum of an objective function.The quantum versions of gradient descent have been investigated and implemented in calculating molecular ground states and optimizing polynomial functions.Based on the quantum gradient descent algorithm and Choi-Jamiolkowski isomorphism,we present approaches to simulate efficiently the nonequilibrium steady states of Markovian open quantum many-body systems.Two strategies are developed to evaluate the expectation values of physical observables on the nonequilibrium steady states.Moreover,we adapt the quantum gradient descent algorithm to solve linear algebra problems including linear systems of equations and matrix-vector multiplications,by converting these algebraic problems into the simulations of closed quantum systems with well-defined Hamiltonians.Detailed examples are given to test numerically the effectiveness of the proposed algorithms for the dissipative quantum transverse Ising models and matrix-vector multiplications.展开更多
With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rej...With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.展开更多
In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of t...In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10-4s,thus meeting the requirements of real-time combat scenarios.展开更多
Integrated optical phased arrays(OPAs),owing to their high integration level and wide-angle beamsteering capability,are a key promising component for 3D/4D sensing and free-space optical communication.However,integrat...Integrated optical phased arrays(OPAs),owing to their high integration level and wide-angle beamsteering capability,are a key promising component for 3D/4D sensing and free-space optical communication.However,integrated OPAs typically employ a single-wavelength laser as the input light source,which limits their application in spectral imaging and secure communication.In this work,we propose and experimentally demonstrate a dual-wavelength coherent beam combining(CBC)scheme using a 64-element integrated OPA.A multiwavelength CBC model is established and validated with two wavelength pairs(1545/1555 and 1535∕1565 nm).Both simulation and experimental results confirm that the beam dispersion intensifies with the steering angle and wavelength separation.To overcome this inherent dispersion issue,we employ a stochastic parallel gradient descent algorithm with two avalanche photodiodes as feedback sensors,achieving an arbitrarily configurable angular separation between the two wavelength beams.Finally,we demonstrate the wide field of view beam-steering capability of the combined beam across a 60 deg(±30 deg)range.We provide a foundational framework for advancing multiwavelength OPA toward applications in spectral imaging and secure optical communications.展开更多
The growing interest in addressing minimax optimization problem has been fueled by recent applications in machine learning.Although extensively studied in the convex–concave regime,where a global solution can be effi...The growing interest in addressing minimax optimization problem has been fueled by recent applications in machine learning.Although extensively studied in the convex–concave regime,where a global solution can be efficiently computed,this paper delves into the minimax problem within the nonconvex–concave setup.We propose an alternating gradient projection algorithm with momentum(M-AGP),belonging to single-loop algorithms that not only are easier to implement but also require only the computation of gradient projection updates.We demonstrate that the proposed algorithm identifies an-stationary point of the nonconvex–strongly concave minimax problem in O(ε-2)iterations,representing the best-known rate in the literature.Finally,we utilize two test problems,namely robust nonlinear regression and an image classification problem,to showcase the efficacy of the proposed algorithm.展开更多
准确求解各支承点的承载力分布是静压导轨结构设计与性能优化的关键。针对多点支承超静定系统的支承力求解问题,传统代数方法的计算维度与复杂度随支承点数量增加而显著上升。为此,提出一种基于梯度下降算法的超静定载荷分布迭代求解方...准确求解各支承点的承载力分布是静压导轨结构设计与性能优化的关键。针对多点支承超静定系统的支承力求解问题,传统代数方法的计算维度与复杂度随支承点数量增加而显著上升。为此,提出一种基于梯度下降算法的超静定载荷分布迭代求解方法。该方法的核心思想,基于刚体运动学假设和刚体静力学线性分布假设,将各支承点的未知反力映射为关于分布斜率与截距的线性函数,从而将高维的力矢量求解降维为极低维的特征参数优化。在此基础上,构建了表征静力学平衡偏差的损失函数,利用梯度下降算法迭代搜索最优参数以最小化平衡偏差。研究表明,该方法有效规避了对高维线性方程组的依赖,实现了计算复杂度与支承点数量的解耦。同时,通过对比工程案例的算法计算结果与有限元仿真(finite element analysis,FEA)结果,证实了该方法兼具良好的精度与可靠性,能够满足工程设计需求。展开更多
基金supported by the Fundamental Research Funds for the Central Universities(No.56XAA17075)
摘要A gradient descent algorithm with adjustable parameter for attitude estimation is developed,aiming at the attitude measurement for small unmanned aerial vehicle(UAV)in real-time flight conditions.The accelerometer and magnetometer are introduced to construct an error equation with the gyros,thus the drifting characteristics of gyroscope can be compensated by solving the error equation utilized by the gradient descent algorithm.Performance of the presented algorithm is evaluated using a self-proposed micro-electro-mechanical system(MEMS)based attitude heading reference system which is mounted on a tri-axis turntable.The on-ground,turntable and flight experiments indicate that the estimation attitude has a good accuracy.Also,the presented system is compared with an open-source flight control system which runs extended Kalman filter(EKF),and the results show that the attitude control system using the gradient descent method can estimate the attitudes for UAV effectively.
基金supported by the National Natural Science Foundation of China(Grant Nos.12075159,12171044,and 12005015)Beijing Natural Science Foundation(Grant No.Z190005)Academy for Multidisciplinary Studies,Capital Normal University,Academician Innovation Platform of Hainan Province,and Shenzhen Institute for Quantum Science and Engineering,Southern University of Science and Technology(Grant No.SIQSE202001)。
摘要The gradient descent approach is the key ingredient in variational quantum algorithms and machine learning tasks,which is an optimization algorithm for finding a local minimum of an objective function.The quantum versions of gradient descent have been investigated and implemented in calculating molecular ground states and optimizing polynomial functions.Based on the quantum gradient descent algorithm and Choi-Jamiolkowski isomorphism,we present approaches to simulate efficiently the nonequilibrium steady states of Markovian open quantum many-body systems.Two strategies are developed to evaluate the expectation values of physical observables on the nonequilibrium steady states.Moreover,we adapt the quantum gradient descent algorithm to solve linear algebra problems including linear systems of equations and matrix-vector multiplications,by converting these algebraic problems into the simulations of closed quantum systems with well-defined Hamiltonians.Detailed examples are given to test numerically the effectiveness of the proposed algorithms for the dissipative quantum transverse Ising models and matrix-vector multiplications.
基金the 2021 Key Project of Natural Science and Technology of Yangzhou Polytechnic Institute,Active Disturbance Rejection and Fault-Tolerant Control of Multi-Rotor Plant ProtectionUAV Based on QBall-X4(Grant Number 2021xjzk002).
摘要With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.
基金National Natural Science Foundation of China(62373187)Forward-looking Layout Special Projects(ILA220591A22)。
摘要In the field of calculating the attack area of air-to-air missiles in modern air combat scenarios,the limitations of existing research,including real-time calculation,accuracy efficiency trade-off,and the absence of the three-dimensional attack area model,restrict their practical applications.To address these issues,an improved backtracking algorithm is proposed to improve calculation efficiency.A significant reduction in solution time and maintenance of accuracy in the three-dimensional attack area are achieved by using the proposed algorithm.Furthermore,the age-layered population structure genetic programming(ALPS-GP)algorithm is introduced to determine an analytical polynomial model of the three-dimensional attack area,considering real-time requirements.The accuracy of the polynomial model is enhanced through the coefficient correction using an improved gradient descent algorithm.The study reveals a remarkable combination of high accuracy and efficient real-time computation,with a mean error of 91.89 m using the analytical polynomial model of the three-dimensional attack area solved in just 10-4s,thus meeting the requirements of real-time combat scenarios.
基金supported by the National Natural Science Foundation of China(Grant Nos.62575305,62305275,12574333,11974258,and 62305388)the Natural Science Foundation of Hunan Province of China(Grant No.2024JJ6473)the Innovation Research Foundation of National University of Defense Technology(Innovation Research Foundation of(NUDT)(Grant No.24-ZZCX-JDZ-18).
摘要Integrated optical phased arrays(OPAs),owing to their high integration level and wide-angle beamsteering capability,are a key promising component for 3D/4D sensing and free-space optical communication.However,integrated OPAs typically employ a single-wavelength laser as the input light source,which limits their application in spectral imaging and secure communication.In this work,we propose and experimentally demonstrate a dual-wavelength coherent beam combining(CBC)scheme using a 64-element integrated OPA.A multiwavelength CBC model is established and validated with two wavelength pairs(1545/1555 and 1535∕1565 nm).Both simulation and experimental results confirm that the beam dispersion intensifies with the steering angle and wavelength separation.To overcome this inherent dispersion issue,we employ a stochastic parallel gradient descent algorithm with two avalanche photodiodes as feedback sensors,achieving an arbitrarily configurable angular separation between the two wavelength beams.Finally,we demonstrate the wide field of view beam-steering capability of the combined beam across a 60 deg(±30 deg)range.We provide a foundational framework for advancing multiwavelength OPA toward applications in spectral imaging and secure optical communications.
基金supported by the National Key R&D Program of China(No.2023YFA1011303)the National Natural Science Foundation of China(Nos.11971083 and 11991024)+1 种基金the Team Project of Innovation Leading Talent in Chongqing(No.CQYC20210309536)the Contract System Project of Chongqing Talent Plan(No.cstc2022ycjh-bgzxm0147).
摘要The growing interest in addressing minimax optimization problem has been fueled by recent applications in machine learning.Although extensively studied in the convex–concave regime,where a global solution can be efficiently computed,this paper delves into the minimax problem within the nonconvex–concave setup.We propose an alternating gradient projection algorithm with momentum(M-AGP),belonging to single-loop algorithms that not only are easier to implement but also require only the computation of gradient projection updates.We demonstrate that the proposed algorithm identifies an-stationary point of the nonconvex–strongly concave minimax problem in O(ε-2)iterations,representing the best-known rate in the literature.Finally,we utilize two test problems,namely robust nonlinear regression and an image classification problem,to showcase the efficacy of the proposed algorithm.
摘要准确求解各支承点的承载力分布是静压导轨结构设计与性能优化的关键。针对多点支承超静定系统的支承力求解问题,传统代数方法的计算维度与复杂度随支承点数量增加而显著上升。为此,提出一种基于梯度下降算法的超静定载荷分布迭代求解方法。该方法的核心思想,基于刚体运动学假设和刚体静力学线性分布假设,将各支承点的未知反力映射为关于分布斜率与截距的线性函数,从而将高维的力矢量求解降维为极低维的特征参数优化。在此基础上,构建了表征静力学平衡偏差的损失函数,利用梯度下降算法迭代搜索最优参数以最小化平衡偏差。研究表明,该方法有效规避了对高维线性方程组的依赖,实现了计算复杂度与支承点数量的解耦。同时,通过对比工程案例的算法计算结果与有限元仿真(finite element analysis,FEA)结果,证实了该方法兼具良好的精度与可靠性,能够满足工程设计需求。