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An algorithm for robust explicit/multi-parametric model predictive control
DOI:10.1016/j.automatica.2012.11.035.png)
摘要
En 中文
A new algorithm for robust explicit/multi-parametric Model Predictive Control (MPC) for uncertain, linear discrete-time systems is proposed. Based on previous work on Dynamic Programming (DP), multi-parametric Programming and Robust Optimization, the proposed algorithm features, (i) a DP reformulations of the MPC optimization problem, (ii) a robust reformulation of the constraints, and (iii) a multi-parametric programming step, where the control variables are obtained as explicit functions of the state variable, such that the state and input constraints are satisfied for all admissible values of the uncertainty. A key feature of the proposed procedure is that, as opposed to previous methods, it only solves a convex multi-parametric programming problem for each stage of the DP procedure. (C) 2012 Elsevier Ltd. All rights reserved.
Keyword:
Explicit/multi-parametric MPC
Model predictive control
Robust control
Multi-parametric programming
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期刊
IF:
5.9
论文数:
1.2W
被引数:
5.2W
机构
引用论文
Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming通过动态和多参数编程对线性离散时间系统进行显式/多参数模型预测控制 (MPC)
AUTOMATICA
IF5.9
Feedback min-max model predictive control using a single linear program: robust stability and the explicit solution使用单个线性程序的反馈最小-最大模型预测控制: 鲁棒稳定性和显式解决方案

