A graph search algorithm for optimal control of hybrid systems
A graph search algorithm for optimal control of hybrid systems
复制标题
混合系统最优控制的图搜索算法
DOI：
10.1109/cdc.2004.1430241
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
O. Stursberg
中科院分区：
文献类型：
--
作者：
O. Stursberg
对于具有非线性连续动态和离散以及连续输入的混合自动机的最优控制，最近提出了一种将图搜索技术与最优控制原理相结合的方法。其主要思想是将非线性规划和混合系统仿真嵌入到选择离散自由度的图搜索算法中。当应用这种方法时，可以观察到，通常大量的几乎相同的混合动力系统的演化被探索，而系统性能没有（或边际）改善。为了获得更好的混合搜索空间的覆盖率，该方法在这里扩展的邻接准则的概念。其原理是从几乎相同的演化集合中确定局部最优轨迹，推迟次优轨迹的评估，从而以较低的努力获得定性不同的解决方案。邻接准则可以用作搜索策略，或者如果接近最优的解决方案就足够了，则可以修剪搜索图。
For optimally controlling hybrid automata with nonlinear continuous dynamics and discrete as well as continuous inputs, an approach combining graph search techniques with principles of optimal control has recently been proposed. The main idea is to embed nonlinear programming and hybrid system simulation into a graph search algorithm that selects the discrete degrees of freedom. When applying this approach, it can be observed that often large numbers of almost identical evolutions of the hybrid system are explored with no (or marginal) improvement of the system performance. In order to obtain a better coverage of the hybrid search space, the method is here extended by the notion of adjacency criteria. The principle is to determine locally optimal trajectories from the set of almost identical evolutions, to postpone the evaluation of suboptimal ones, and thus to obtain qualitatively different solutions with low effort. The adjacency criteria can either be used as a search heuristics or, if a near-optimal solution is sufficient, to prune the search graph.