Reachable set computation of linear systems with nonconvex constraints via convex optimization
Reachable set computation of linear systems with nonconvex constraints via convex optimization
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DOI：
10.1016/j.automatica.2022.110632
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发表时间：
2022-12
期刊：
影响因子：
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通讯作者：
Runqiu Yang;Xinfu Liu
中科院分区：
文献类型：
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作者：
Runqiu Yang;Xinfu Liu
本文讨论了具有非凸控制约束和其它凸控制及状态约束的线性系统的可达集计算问题。我们建议凸的非凸约束的松弛技术。我们证明了在一定的假设下，松弛约束系统在任意给定的最终时刻的可达集都等于原约束系统在同一最终时刻的可达集，有趣的是，即使容许控制集被扩展，它也成立.理论结果使我们能够利用凸优化方法高效、准确地计算原约束系统的可达集。我们将通过两个行星精确着陆的例子来验证和应用理论结果的可达集计算。
This paper addresses the reachable set computation of a linear system with a nonconvex control constraint and other convex control and state constraints. We propose to convexify the nonconvex constraint by a relaxation technique. We prove that the reachable set of the relaxed constrained system at any given final time is equal to that of the original constrained system at the same final time under certain assumptions, and interestingly it holds even though the admissible control set is expanded. The theoretical result can enable us to use convex optimization to efficiently and accurately compute the reachable set of the original constrained system. We will verify and apply the theoretical result to reachable set computation via two planetary precision landing examples.