Convexifying State-Constrained Optimal Control Problem

• 成果类型: Article
• 署名作者: Lee, Donggun; Deka, Shankar A.; Tomlin, Claire J.
• 署名单位: University of California System; University of California Berkeley; Royal Institute of Technology; University of California System; University of California Berkeley
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3221704
• 发表日期: 2023
• 页码: 5608-5615
• 关键词: Nonlinear control systems; optimal control

摘要

This article presents a method that convexifies state-constrained optimal control problems in the control-input space. The proposed method enables convex programming methods to find the globally optimal solution even if costs and control constraints are nonconvex in control and convex in state, dynamics is nonaffine in control and convex in state, and state constraints are convex in state. Under the above conditions, generic methods do not guarantee to find optimal solutions, but the proposed method does. The proposed approach is demonstrated in a 16-D navigation example.