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Efficient optimization method for variable-specific-impulse low-thrust trajectories with shutdown constraint

Science China(Technological Sciences) 2022年第3期65卷 581-594页

作者： JIA FeiDa QIAO Dong HAN HongWei LI XiangYu School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration Ministry of Industry and Information TechnologyBeijing 100081China

This paper develops a sequential convex programming(SCP)-based method to solve the minimum-fuel variable-specific-impulse low-thrust transfer problem considering shutdown constraint,with emphasize on improving the computational efficiency.The variable parameter engine is more applicable for many low-thrust scenarios,therefore,both a continuously variable model and a ladder variable model are adopted.First,the original problem is convexified by processing the constraint feasible domain,which is composed of the nonlinear dynamic equations and second-order equality constraint,into convex sets.Then,the approximation is generated to close the optimal solution of the low-thrust problem by iteratively solving the convexified subproblem.Moreover,the switching self-detection and adaptive node refinement methods are presented,which can improve the accuracy of the solution and accelerate the convergence during the approximation process and is especially necessary and effective in the scenarios with shutdown constraint.In numerical simulations,the comparison with the homotopic approach shows that the proposed method only needs 4%computational time as that of the homotopic approach,and two variable-specificimpulse examples further demonstrate the effectiveness and efficiency of the proposed method.

关键词： low-thrust trajectory variable-specific-impulse shutdown constraint sequential convex programming switching self-detection and adaptive node refinement

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An efficient method for collision-free and jerk-constrained trajectory generation with sparse desired way-points for a flying robot

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Science China(Technological Sciences) 2021年第8期64卷 1719-1731页

作者： CHEN YongXue DONG Wei DING Ye State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong UniversityShanghai200240China

In this paper,an efficient approach is developed to plan jerk-constrained smooth trajectories passing through desired way-points with allowable accuracy for an autonomous quadrotor.First,based on the B-spline model,we introduce the sequential convex programming(SCP)into the flexible path planning method to satisfy the way-points constraints.By approximating the quadrotor and obstacles as spheres and directed planes,the length-optimal and collision-free path planning problem is formulated as a nonconvex optimization problem and solved by SCP.The initial C^(3) continuous path curve for optimization is constructed efficiently based on a proposed strategy of generating new way-points near the obstacles without the need to calculate the embedding distance between the curve and the obstacles.On this basis,the time-optimal speed planning problem is addressed in two steps.In the first step,the forward-backward approach is introduced to solve the problem under the chord error,velocity,and acceleration constraints by changing the variables and deforming the constraints.Then by relaxing the constraints appropriately,the problem under jerk constraints is formulated into a linear programming(LP)problem.The feasibility of the proposed approach is verified through simulations and an indoor navigation experiment.The proposed approach can generate a C^(3) continuous collision-free trajectory that passes through the sparse desired way-points with allowable accuracy while guaranteeing the chord error,velocity,acceleration,and jerk constraints.When the number of sample points is 3000,the proposed speed planning method reduces the calculation time by 40%compared to an existing method.

关键词： collision avoidance speed optimization motion planning sequential convex programming quadrotor

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Efficient solution of large mathematical programs arising in engineering design optimization with the method of moving asymptotes

Efficient solution of large mathematical programs arising in...

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The Fourth World Congress of Structural and Multidisciplinary Optimization

作者： Christian Zillober Mathematisches Institut Universitt Bayreuth D-95440 BayreuthGermany

＜正＞In mechanical design problems, the method of moving asymptotes is a popular tool to solve the arising optimization problems. For large problems, however, the method often needs too much storage and computing time in its traditional formulation. Therefore, a new approach to solve the subproblems has been defined which gives the possibility to exploit sparsity in the original problem and does not create dense structure itself. Several subapproaches with different advantages and disadvantages are possible. The decision for the best possibility can be done by the computer. A central point of this paper will be the description of SCPIP, the FORTRAN77 realization of these approaches. Up to now the method has been mainly applied to weight optimization and topology design.

关键词： convex approximation methods method of moving asymptotes sequential convex programming structural optimization large-scale optimization

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