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Autonomous trajectory planning for space vehicles with a Newton-Kantorovich/convex programming approach

机译:具有牛顿 - kantorovich /凸编程方法的空间车辆的自主轨迹规划

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摘要

Space maneuverings of the space vehicle require the capability of onboard trajectory planning. Convex programming based optimization strategy gets much attention in the design of trajectory planning methods with deterministic convergence properties. Due to the nonlinear dynamics, space-trajectory planning problems are always non-convex and difficult to be solved by the convex programming approach directly. This paper presents a Newton-Kantorovich/convex programming (N-K/CP) approach, based on the combination of the convex programming and the Newton-Kantorovich (N-K) method, to solve the nonlinear and non-convex space-trajectory planning problem. This trajectory planning problem is formulated as a nonlinear optimal control problem. By linearization and relaxation techniques, the nonlinear optimal control problem is convexified as a convex programming problem, which can be solved efficiently with convex programming solvers. For the linearized convex optimization problem, N-K method is introduced to design an iterative solving algorithm, the solution of which approximates the original trajectory planning problem with high accuracy. The convergence of the proposed N-K/CP approach is proved, and the effectiveness is demonstrated by numerical experiments and comparisons with other state-of-the-art methods.
机译:太空车辆的空间机动需要车载轨迹规划的能力。基于Convex编程的优化策略在具有确定性收敛性的轨迹规划方法的设计中得到了很多关注。由于非线性动力学,空间轨迹规划问题总是非凸,并且难以通过凸编程方法直接解决。本文提出了一种基于凸编程和牛顿 - kantorovich(n-k)方法的组合,旨在解决非线性和非凸的空间轨迹规划问题的Newton-kantorovich / convex编程(n-k / cp)方法。该轨迹规划问题被制定为非线性最佳控制问题。通过线性化和放松技术,凸出的非线性最佳控制问题被凸出为凸编程问题,这可以用凸编程求解器有效地解决。对于线性化凸优化问题,引入N-K方法以设计迭代求解算法,其解决方案近似于高精度的原始轨迹规划问题。证明了所提出的N-K / CP方法的收敛性,通过数值实验和与其他最先进的方法的比较证明了有效性。

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