Scalable Computation of Robust Control Invariant Sets of Nonlinear Systems

• 成果类型: Article
• 署名作者: Schaefer, Lukas; Gruber, Felix; Althoff, Matthias
• 署名单位: Technical University of Munich; Bosch
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2023.3275305
• 发表日期: 2024
• 页码: 755-770
• 关键词: Invariant sets; nonlinear control systems; scalability; Robust control; Cyber-physical systems; safety

摘要

Ensuring robust constraint satisfaction for an infinite-time horizon is a challenging, yet crucial task when deploying safety-critical systems. In this article, we address this issue by synthesizing robust control invariant sets of perturbed nonlinear sampled-data systems. This task can be encoded as a nonconvex program that we approximate by a tailored, computationally efficient successive convexification algorithm. Based on the zonotopic representation of invariant sets, we obtain an updated candidate for the invariant set and the invariance-enforcing controller by solving a single convex program. To obtain a possibly large region of safe operation, our algorithm is designed so that the sequence of candidate invariant sets is volume-wise monotonically increasing. We demonstrate the efficacy and scalability of our approach using a broad range of nonlinear control systems from the literature with up to 20 dimensions.