论文标题
在非线性系统上的定量两相触及避免问题的大约最佳控制器
Approximately Optimal Controllers for Quantitative Two-Phase Reach-Avoid Problems on Nonlinear Systems
论文作者
论文摘要
目前的工作涉及非线性控制系统上的定量两相避免问题。这类最佳控制问题要求工厂的状态连续访问两个（而不是一个）目标集，同时最大程度地减少规定的成本功能。正如我们所说明的，将问题细分为两个明显的经典避免范围任务的天真方法通常不会导致最佳解决方案。相比之下，我们证明，通过连续解决两个特殊的定量避免问题问题来获得最佳控制器。此外，我们提出了一种基于符号最佳控制的完全自动化方法，可实际合成所考虑的问题类别的近似于采样DATA非线性植物的最佳控制器。包裹交付和飞机路由任务的实验结果证实了我们方法的实用性。
The present work deals with quantitative two-phase reach-avoid problems on nonlinear control systems. This class of optimal control problem requires the plant's state to visit two (rather than one) target sets in succession while minimizing a prescribed cost functional. As we illustrate, the naive approach, which subdivides the problem into the two evident classical reach-avoid tasks, usually does not result in an optimal solution. In contrast, we prove that an optimal controller is obtained by consecutively solving two special quantitative reach-avoid problems. In addition, we present a fully-automated method based on Symbolic Optimal Control to practically synthesize for the considered problem class approximately optimal controllers for sampled-data nonlinear plants. Experimental results on parcel delivery and on an aircraft routing mission confirm the practicality of our method.
