Optimizing prediction dynamics for robust MPC
Optimizing prediction dynamics for robust MPC
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DOI：
10.1109/tac.2005.858679
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发表时间：
2005-11
影响因子：
6.8
通讯作者：
M. Cannon;B. Kouvaritakis
中科院分区：
文献类型：
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作者：
M. Cannon;B. Kouvaritakis
针对具有多面体不确定性的约束线性系统，给出了优化动态反馈律的凸公式。我们证明了当存在时，包含任何选择的静态反馈增益的动态反馈律下的对象状态的最大不变椭球集等于任何线性反馈律下的最大不变椭球集。动态控制器及其关联的不变集定义了计算上有效的鲁棒模型预测控制(MPC)律，其中预测动力学属于多面体不确定集。
A convex formulation is derived for optimizing dynamic feedback laws for constrained linear systems with polytopic uncertainty. We show that, when it exists, the maximal invariant ellipsoidal set for the plant state under a dynamic feedback law incorporating any chosen static feedback gain is equal to the maximal invariant ellipsoidal set under any linear feedback law. The dynamic controller and its associated invariant set define a computationally efficient robust model predictive control (MPC) law with prediction dynamics belonging to a polytopic uncertainty set.