模型预测控制
参数化复杂度
同态变换
控制理论(社会学)
正多边形
顶点(图论)
仿射变换
乘法函数
数学优化
数学
不变(物理)
计算机科学
控制(管理)
算法
数学分析
纯数学
组合数学
几何学
人工智能
图形
数学物理
作者
Mario E. Villanueva,Matthias A. Müller,Boris Houska
出处
期刊:Cornell University - arXiv
日期:2022-01-01
标识
DOI:10.48550/arxiv.2208.12554
摘要
This paper is about robust Model Predictive Control (MPC) for linear systems with additive and multiplicative uncertainty. A novel class of configuration-constrained polytopic robust forward invariant tubes is introduced, which admit a joint parameterization of their facets and vertices. They are the foundation for the development of novel Configuration-Constrained Tube MPC (CCTMPC) controllers that freely optimize the shape of their polytopic tube, subject to conic vertex configuration constraints, as well as associated vertex control laws by solving convex optimization problems online. It is shown that CCTMPC is -- under appropriate assumptions -- systematically less conservative than Rigid- and Homothetic- Tube MPC. Additionally, it is proven that there exist control systems for which CCTMPC is less conservative than Elastic Tube MPC, Disturbance Affine Feedback MPC, and Fully Parameterized Tube MPC.
科研通智能强力驱动
Strongly Powered by AbleSci AI