论文标题
可行的顺序线性编程算法，并应用于时间 - 最佳路径计划问题
A Feasible Sequential Linear Programming Algorithm with Application to Time-Optimal Path Planning Problems
论文作者
论文摘要
在本文中，我们提出了一种可行的顺序线性编程（FSLP）算法，该算法应用于通过直接多重射击离散化获得的时间优势控制问题（TOCP）。该方法是由TOCP引起的，具有非线性约束，这些限制在机电系统的运动计划中产生。该算法应用了信任区域全球化策略，以确保全球融合。对于完全确定的问题，我们的算法提供了局部二次收敛。此外，该算法可以使所有可行的迭代均可在次优的，可行的解决方案下提前终止。通过使用约束的评估，即零级信息，通过有效的迭代策略来实现这种额外的可行性。可行性迭代的融合可以通过减少信任区域半径来实现。这些可行性迭代可保持一般非线性程序（NLP）的可行性。因此，该算法适用于一般NLP。我们证明了算法的效率和可行性更新策略，该策略是架空起重机运动计划模拟案例的TOCP。
In this paper, we propose a Feasible Sequential Linear Programming (FSLP) algorithm applied to time-optimal control problems (TOCP) obtained through direct multiple shooting discretization. This method is motivated by TOCP with nonlinear constraints which arise in motion planning of mechatronic systems. The algorithm applies a trust-region globalization strategy ensuring global convergence. For fully determined problems our algorithm provides locally quadratic convergence. Moreover, the algorithm keeps all iterates feasible enabling early termination at suboptimal, feasible solutions. This additional feasibility is achieved by an efficient iterative strategy using evaluations of constraints, i.e., zero-order information. Convergence of the feasibility iterations can be enforced by reduction of the trust-region radius. These feasibility iterations maintain feasibility for general Nonlinear Programs (NLP). Therefore, the algorithm is applicable to general NLPs. We demonstrate our algorithm's efficiency and the feasibility update strategy on a TOCP of an overhead crane motion planning simulation case.
