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Entry trajectory optimization for cross-domain morphing vehicles using oscillation-avoidance-based multistage trust-region sequential convex programming 认领 引用
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作者 Zheng LI Zheng FANG +1 位作者 Zhenyue JIA Jianqiao YU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期310-333,共24页
This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(C... This paper develops an Oscillation-avoidance-based Multistage Trust-region Sequential Convex Programming(OMTSCP)method for the highly nonlinear entry trajectory optimization problem of Cross-Domain Morphing Vehicles(CDMVs).The decoupling of states and controls for complex nonlinear dynamics is achieved by defining new control and state variables.A series of sub convex problems is formulated by successive linearization and discretization of the constraints.The proposed Trust-region Sequential Convex Programming(TSCP)scheme consists of three stages:an initial guess generation stage,a basic solution stage,and an optimal solution stage.An approach to penalize the dynamic relaxation is firstly developed to obtain an initial guess with considerable accuracy and significantly improve the robustness of the algorithm by overcoming the drawbacks of potential artificial infeasibility.The oscillation phenomenon of the TSCP method under rectangular trust region is then investigated,and a novel N-shape-based oscillation identification method is proposed to identify the oscillation accurately.Finally,an oscillation-avoidance method based on the sort trust-region is proposed to improve the convergence of the TSCP algorithm.Numerical comparisons of the proposed method and a typical TSCP method,as well as the morphing and fixed-morphing vehicles are provided to demonstrate the effectiveness and efficiency of the proposed method and the performance advantages of the morphing vehicle.The robustness of the method is further verified by Monte Carlo simulation. 展开更多
关键词 Convex optimization Cross-domain vehicle Entry trajectory optimization Morphing vehicle Multistage Oscillation phenomenon Trust-region sequential convex programming
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Safe flight corridor constrained sequential convex programming for efficient trajectory generation of fixed-wing UAVs 认领 引用 被引量：6
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作者 Jing SUN Guangtong XU +2 位作者 Zhu WANG Teng LONG Jingliang SUN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第1期537-550,共14页
Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequent... Generating dynamically feasible trajectory for fixed-wing Unmanned Aerial Vehicles(UAVs)in dense obstacle environments remains computationally intractable.This paper proposes a Safe Flight Corridor constrained Sequential Convex Programming(SFC-SCP)to improve the computation efficiency and reliability of trajectory generation.SFC-SCP combines the front-end convex polyhedron SFC construction and back-end SCP-based trajectory optimization.A Sparse A*Search(SAS)driven SFC construction method is designed to efficiently generate polyhedron SFC according to the geometric relation among obstacles and collision-free waypoints.Via transforming the nonconvex obstacle-avoidance constraints to linear inequality constraints,SFC can mitigate infeasibility of trajectory planning and reduce computation complexity.Then,SCP casts the nonlinear trajectory optimization subject to SFC into convex programming subproblems to decrease the problem complexity.In addition,a convex optimizer based on interior point method is customized,where the search direction is calculated via successive elimination to further improve efficiency.Simulation experiments on dense obstacle scenarios show that SFC-SCP can generate dynamically feasible safe trajectory rapidly.Comparative studies with state-of-the-art SCP-based methods demonstrate the efficiency and reliability merits of SFC-SCP.Besides,the customized convex optimizer outperforms off-the-shelf optimizers in terms of computation time. 展开更多
关键词 Fixed-wing unmanned aerial vehicle Efficient trajectory planning Safe flight corridor Sequential convex programming Customized convex optimizer
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A POLYNOMIAL PREDICTOR-CORRECTOR INTERIOR-POINT ALGORITHM FOR CONVEX QUADRATIC PROGRAMMING 认领 引用 被引量：6
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作者 余谦 黄崇超 江燕 《Acta Mathematica Scientia》 SCIE 2006年第2期265-270,共6页
This article presents a polynomial predictor-corrector interior-point algorithm for convex quadratic programming based on a modified predictor-corrector interior-point algorithm. In this algorithm, there is only one c... This article presents a polynomial predictor-corrector interior-point algorithm for convex quadratic programming based on a modified predictor-corrector interior-point algorithm. In this algorithm, there is only one corrector step after each predictor step, where Step 2 is a predictor step and Step 4 is a corrector step in the algorithm. In the algorithm, the predictor step decreases the dual gap as much as possible in a wider neighborhood of the central path and the corrector step draws iteration points back to a narrower neighborhood and make a reduction for the dual gap. It is shown that the algorithm has O（√nL） iteration complexity which is the best result for convex quadratic programming so far. 展开更多
关键词 Convex quadratic programming predictor-corrector interior-point algorithm
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A Combined Homotopy Infeasible Interior-Point Method for Convex Nonlinear Programming 认领 引用 被引量：3
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作者 杨轶华 吕显瑞 刘庆怀 《Northeastern Mathematical Journal》 2006年第2期188-192,共5页
In this paper, on the basis of the logarithmic barrier function and KKT conditions, we propose a combined homotopy infeasible interior-point method （CHIIP） for convex nonlinear programming problems. For any convex n... In this paper, on the basis of the logarithmic barrier function and KKT conditions, we propose a combined homotopy infeasible interior-point method （CHIIP） for convex nonlinear programming problems. For any convex nonlinear programming, without strict convexity for the logarithmic barrier function, we get different solutions of the convex programming in different cases by CHIIP method. 展开更多
关键词 convex nonlinear programming infeasible interior point method homotopy method global convergence
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PARALLEL MULTIPLICATIVE ITERATIVE METHODS FOR CONVEX PROGRAMMING 认领 引用 被引量：1
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作者 Chen zhong Fei Pusheng 《Acta Mathematica Scientia》 SCIE 1997年第2期205-210,共6页
In this paper,we present two parallel multiplicative algorithms for convex programming.If the objective function has compact level sets and has a locally Lipschitz continuous gradient,we discuss convergence of the alg... In this paper,we present two parallel multiplicative algorithms for convex programming.If the objective function has compact level sets and has a locally Lipschitz continuous gradient,we discuss convergence of the algorithms.The proofs are essentially based on the results of sequential methods shown by Eggermontt[1]. 展开更多
关键词 parallel algorithm convex programming
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Checking weak and strong optimality of the solution to interval convex quadratic program 认领 引用
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作者 XIA Meng-xue LI Miao-miao +1 位作者 ZHANG Ben LI Hao-hao 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2021年第2期172-186,共15页
In this paper,we investigate three canonical forms of interval convex quadratic pro-gramming problems.Necessary and suficient conditions for checking weak and strong optimality of given vector corresponding to various... In this paper,we investigate three canonical forms of interval convex quadratic pro-gramming problems.Necessary and suficient conditions for checking weak and strong optimality of given vector corresponding to various forms of feasible region,are established respectively.By using the concept of feasible direction,these conditions are formulated in the form of linear systems with both equations and inequalities.In addition,we provide two specific examples to illustrate the efficiency of the conditions. 展开更多
关键词 interval convex quadratic program weakly optimal solution strongly optimal solution feasible directions
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NEWTON METHOD FOR SOLVING A CLASS OF SMOOTH CONVEX PROGRAMMING 认领 引用
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作者 姚奕荣 张连生 +1 位作者 韩伯顺 DAI Shi-qiang 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2005年第11期1491-1498,共8页
An algorithm for solving a class of smooth convex programming is given. Using smooth exact multiplier penalty function, a smooth convex programming is minimized to a minimizing strongly convex function on the compact ... An algorithm for solving a class of smooth convex programming is given. Using smooth exact multiplier penalty function, a smooth convex programming is minimized to a minimizing strongly convex function on the compact set was reduced. Then the strongly convex function with a Newton method on the given compact set was minimized. 展开更多
关键词 convex programming Newton method KKT multiplier
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Asymptotic Performance of Sparse Signal Detection Using Convex Programming Method 认领 引用
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作者 LEI Chuan ZHANG Jun 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2012年第3期396-405,共10页
The detection of sparse signals against background noise is considered. Detecting signals of such kind is difficult since only a small portion of the signal carries information. Prior knowledge is usually assumed to e... The detection of sparse signals against background noise is considered. Detecting signals of such kind is difficult since only a small portion of the signal carries information. Prior knowledge is usually assumed to ease detection. In this paper, we consider the general unknown and arbitrary sparse signal detection problem when no prior knowledge is available. Under a Ney- man-Pearson hypothesis-testing framework, a new detection scheme is proposed by combining a generalized likelihood ratio test （GLRT）-Iike test statistic and convex programming methods which directly exploit sparsity in an underdetermined system of linear equations. We characterize large sample behavior of the proposed method by analyzing its asymptotic performance. Specifically, we give the condition for the Chernoff-consistent detection which shows that the proposed method is very sensitive to the norm energy of the sparse signals. Both the false alam rate and the miss rate tend to zero at vanishing signal-to-noise ratio （SNR）, as long as the signal energy grows at least logarithmically with the problem dimension. Next we give a large deviation analysis to characterize the error exponent for the Neyman-Pearson detection. We derive the oracle error exponent assuming signal knowledge. Then we explicitly derive the error exponent of the proposed scheme and compare it with the oracle exponent. We complement our study with numerical experiments, showing that the proposed method performs in the vicinity of the likelihood ratio test （LRT） method in the finite sample scenario and the error probability degrades exponentially with the number of observations. 展开更多
关键词 signal detection convex programming asymptotic analysis signal reconstruction sparse signals
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Stochastic level-value approximation for quadratic integer convex programming 认领 引用
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作者 彭拯 邬冬华 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2008年第6期801-809,共9页
We propose a stochastic level value approximation method for a quadratic integer convex minimizing problem in this paper. This method applies an importance sampling technique, and make use of the cross-entropy method ... We propose a stochastic level value approximation method for a quadratic integer convex minimizing problem in this paper. This method applies an importance sampling technique, and make use of the cross-entropy method to update the sample density functions. We also prove the asymptotic convergence of this algorithm, and report some numerical results to illuminate its effectiveness. 展开更多
关键词 quadratic integer convex programming stochastic level value approximation cross-entropy method asymptotic convergence
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Predictor-corrector interior-point algorithm for linearly constrained convex programming 认领 引用
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作者 LIANG Xi-ming 《Journal of Central South University》 SCIE EI CAS 2001年第3期208-212,共5页
Active set method and gradient projection method are curre nt ly the main approaches for linearly constrained convex programming.Interior-po int method is one of the most effective choices for linear programming.In th... Active set method and gradient projection method are curre nt ly the main approaches for linearly constrained convex programming.Interior-po int method is one of the most effective choices for linear programming.In the p aper a predictor-corrector interior-point algorithm for linearly constrained c onvex programming under the predictor-corrector motivation was proposed.In eac h iteration,the algorithm first performs a predictor-step to reduce the dualit y gap and then a corrector-step to keep the points close to the central traject ory.Computations in the algorithm only require that the initial iterate be nonn egative while feasibility or strict feasibility is not required.It is proved th at the algorithm is equivalent to a level-1 perturbed composite Newton method.Numerical experiments on twenty-six standard test problems are made.The result s show that the proposed algorithm is stable and robust. 展开更多
关键词 linearly constrained convex programming predictor corrector interior point algorithm numerical experiment
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Study on the Splitting Methods for Separable Convex Optimization in a Unified Algorithmic Framework 认领 引用
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作者 Bingsheng He 《Analysis in Theory and Applications》 CSCD 2020年第3期262-282,共21页
It is well recognized the convenience of converting the linearly constrained convex optimization problems to a monotone variational inequality.Recently,we have proposed a unified algorithmic framework which can guide ... It is well recognized the convenience of converting the linearly constrained convex optimization problems to a monotone variational inequality.Recently,we have proposed a unified algorithmic framework which can guide us to construct the solution methods for solving these monotone variational inequalities.In this work,we revisit two full Jacobian decomposition of the augmented Lagrangian methods for separable convex programming which we have studied a few years ago.In particular,exploiting this framework,we are able to give a very clear and elementary proof of the convergence of these solution methods. 展开更多
关键词 Convex programming augmented Lagrangian method multi-block separable model Jacobian splitting unified algorithmic framework.
A POTENTIAL REDUCTION ALGORITHM FOR LINEARLY CONSTRAINED CONVEX PROGRAMMING 认领 引用
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作者 Liang XimingCollege of Information Science & Engineering,Central South Univ.,Changsha 410083. 《Applied Mathematics(A Journal of Chinese Universities)》 2001年第4期439-445,共7页
A potential reduction algorithm is proposed for optimization of a convex function subject to linear constraints.At each step of the algorithm,a system of linear equations is solved to get a search direction and the Ar... A potential reduction algorithm is proposed for optimization of a convex function subject to linear constraints.At each step of the algorithm,a system of linear equations is solved to get a search direction and the Armijo's rule is used to determine a stepsize.It is proved that the algorithm is globally convergent.Computational results are reported. 展开更多
关键词 Potential reduction algorithm linearly constrained convex programming global convergence numerical experiments.
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A Wide Neighborhood Arc-Search Interior-Point Algorithm for Convex Quadratic Programming 认领 引用 被引量：2
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作者 YUAN Beibei ZHANG Mingwang HUANG Zhengwei 《Wuhan University Journal of Natural Sciences》 CAS CSCD 2017年第6期465-471,共7页
In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the ent... In this paper, we propose an arc-search interior-point algorithm for convex quadratic programming with a wide neighborhood of the central path, which searches the optimizers along the ellipses that approximate the entire central path. The favorable polynomial complexity bound of the algorithm is obtained, namely O（nlog（（ x^0）~TS^0/ε）） which is as good as the linear programming analogue. Finally, the numerical experiments show that the proposed algorithm is efficient. 展开更多
关键词 arc-search interior-point algorithm polynomial complexity convex quadratic programming
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Fast First-Order Methods for Minimizing Convex Composite Functions 认领 引用
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作者 Qipeng Li Hongwei Liu Zexian Liu 《Journal of Harbin Institute of Technology(New Series)》 CAS 2019年第6期46-52,共7页
Two new versions of accelerated first-order methods for minimizing convex composite functions are proposed. In this paper, we first present an accelerated first-order method which chooses the step size 1/ Lk to be 1/ ... Two new versions of accelerated first-order methods for minimizing convex composite functions are proposed. In this paper, we first present an accelerated first-order method which chooses the step size 1/ Lk to be 1/ L0 at the beginning of each iteration and preserves the computational simplicity of the fast iterative shrinkage-thresholding algorithm. The first proposed algorithm is a non-monotone algorithm. To avoid this behavior, we present another accelerated monotone first-order method. The proposed two accelerated first-order methods are proved to have a better convergence rate for minimizing convex composite functions. Numerical results demonstrate the efficiency of the proposed two accelerated first-order methods. 展开更多
关键词 first-order method iterative shrinkage-thresholding algorithm convex programming adaptive restart composite functions.
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The Second-Order Differential Equation System with the Feedback Controls for Solving Convex Programming 认领 引用
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作者 Xingxu Chen Li Wang +1 位作者 Juhe Sun Yanhong Yuan 《Open Journal of Applied Sciences》 2022年第6期977-989,共13页
In this paper, we establish the second-order differential equation system with the feedback controls for solving the problem of convex programming. Using Lagrange function and projection operator, the equivalent opera... In this paper, we establish the second-order differential equation system with the feedback controls for solving the problem of convex programming. Using Lagrange function and projection operator, the equivalent operator equations for the convex programming problems under the certain conditions are obtained. Then a second-order differential equation system with the feedback controls is constructed on the basis of operator equation. We prove that any accumulation point of the trajectory of the second-order differential equation system with the feedback controls is a solution to the convex programming problem. In the end, two examples using this differential equation system are solved. The numerical results are reported to verify the effectiveness of the second-order differential equation system with the feedback controls for solving the convex programming problem. 展开更多
关键词 Convex Programming Lagrange Function Projection Operator Second-Order Differential Equation
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Online midcourse guidance method for intercepting high-speed gliding target 认领 引用 被引量：1
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作者 ZHANG Jinlin LI Jiong +3 位作者 YE Jikun LEI Humin LI Wanli HE Yangchao 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2025年第5期1374-1388,共15页
In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse ... In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse guidance problem is transformed into a continuous time optimization problem.Secondly,the problem is transformed into a discrete convex programming problem by affine control variable relaxation,Gaussian pseudospectral discretization and constraints linearization.Then,the off-line midcourse guidance trajectory is generated before midcourse guidance.It is used as the initial reference trajectory for online correction of midcourse guidance.An online guidance framework is used to eliminate the error caused by calculation of guidance instruction time.And the design of discrete points decreases with flight time to improve the solving efficiency.In addition,it is proposed that the terminal guidance capture is used innovatively space to judge the success of midcourse guidance.Numerical simulation shows the feasibility and effectiveness of the proposed method. 展开更多
关键词 convex programming capture space online midcourse guidance interception
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SOLVING CONVEX QUADRATIC PROGRAMMING BY POTENTIAL-REDUCTION INTERIOR-POINT ALGORITHM 认领 引用
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作者 LIANG Xi-ming MA Long-hua QIAN Ji-xin 《Journal of Zhejiang University Science》 2001年第1期67-71,共5页
The solution of quadratic programming problems is an important issue in the field of mathematical programming and industrial applications.In this paper,we solve convex quadratic programming by a potential-reduction in... The solution of quadratic programming problems is an important issue in the field of mathematical programming and industrial applications.In this paper,we solve convex quadratic programming by a potential-reduction interior-point algorithm.It is proved that the potential-reduction interior-point algorithm is globally convergent.Some numerical experiments were made. 展开更多
关键词 potential-reduction interior-point algorithm convex quadratic programming convergence numerical experiments
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Multi-target spacecraft mission design using convex optimization and binary integer programming 认领 引用
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作者 Jack Yarndley Harry Holt Roberto Armellin 《Astrodynamics》 EI CSCD 2026年第1期139-163,共25页
The optimal design of multi-target rendezvous and flyby missions is challenging due to the combination of traditional spacecraft trajectory optimization and high-dimensional combinatorial problems.The typical approach... The optimal design of multi-target rendezvous and flyby missions is challenging due to the combination of traditional spacecraft trajectory optimization and high-dimensional combinatorial problems.The typical approach to these problems generally requires large-scale global search techniques or simplified approximations relying on large amounts of manual labour to be performant.However,global search techniques are generally difficult to use in time-or cost-constrained scenarios due to their computational expense.This work proposes a novel combination of computationally efficient stages which work together to form a nested global optimization approach for multi-target mission design.The multi-target problem is split into separate combinatorial and optimal control subproblems,which are recursively solved:the combinatorial problem using a novel Binary Integer Programming(BIP)formulation with fixed rendezvous timings obtaining optimal rendezvous ordering,and the optimal control problem with an adaptive-mesh Sequential Convex Programming(SCP)formulation obtaining optimal rendezvous timings for a fixed rendezvous ordering.These stages work recursively in tandem to improve the inputs to each subsequent stage until convergence is obtained.This methodology is demonstrated to offer state-of-the-art performance when applied to the Global Trajectory Optimization Competition 12(GTOC 12)problem,to which several new best-known solutions are found. 展开更多
关键词 trajectory optimization direct methods binary integer programming(BIP) convex programming
Real-time autonomous guidance generation around small bodies via Sequential Convex Programming 认领 引用
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作者 Enrico Belloni Michèle Lavagna 《Astrodynamics》 EI CSCD 2026年第2期319-337,共19页
This paper introduces a novel approach to real-time convex guidance generation for spacecraft navigating in proximity to small celestial bodies,such as asteroids or small moons.The proposed method leverages Sequential... This paper introduces a novel approach to real-time convex guidance generation for spacecraft navigating in proximity to small celestial bodies,such as asteroids or small moons.The proposed method leverages Sequential Convex Programming(SCP)techniques to model and navigate irregular gravity fields encountered near these bodies,addressing the strong nonlinearities by iteratively refining a convex guidance sub-problem.The key contribution is the development of an adaptive algorithm that autonomously determines the optimal time of flight and dynamically adjusts to the gravitational environment,enabling spacecraft to autonomously generate robust guidance trajectories in real time including a non-convex collision avoidance constraint.The algorithm is developed in library-free C code to be ready for real-time embedded implementation and gain a realistic understanding on possible onboard application.The efficacy of the proposed method is validated for both asteroids and small moons through numerical simulations including sliding-mode close-loop control,showcasing high accuracy,computational efficiency,and flexibility to different environments. 展开更多
关键词 sequential convex programming(SCP) real-time trajectory optimization asteroid exploration model predictive control(MPC)
CONTINUUM TOPOLOGY OPTIMIZATION FOR MONOLITHIC COMPLIANT MECHANISMS OF MICRO-ACTUATORS 认领 引用 被引量：6
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作者 Luo Zhen Du Yixian +2 位作者 Chen Liping Yang Jingzhou Karim Abdel-Malek 《Acta Mechanica Solida Sinica》 SCIE EI 2006年第1期58-68,共11页
A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffnes... A multi-objective scheme for structural topology optimization of distributed compliant mechanisms of micro-actuators in MEMS condition is presented in this work, in which mechanical flexibility and structural stiffness are both considered as objective functions. The compliant micro-mechanism developed in this way can not only provide sufficient output work but also have sufficient rigidity to resist reaction forces and maintain its shape when holding the work-piece. A density filtering approach is also proposed to eliminate numerical instabilities such as checkerboards, mesh-dependency and one-node connected hinges occurring in resulting mechanisms. SIMP is used as the interpolation scheme to indicate the dependence of material modulus on element-regularized densities. The sequential convex programming method, such as the method of moving asymptotes （MMA）, is used to solve the optimization problem. The validation of the presented methodologies is demonstrated by a typical numerical example. 展开更多
关键词 structural optimization topology optimization compliant mechanisms microactuators filtering approach convex programming
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