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A robust distributed model predictive control algorithm
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DOI：10.1016/j.jprocont.2011.07.002.png)
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Although distributed model predictive control (DMPC) has received significant attention in the literature, the robustness of DMPC with respect to model errors has not been explicitly addressed. In this paper, a novel online algorithm that deals explicitly with model errors for DMPC is proposed. The algorithm requires decomposing the entire system into N subsystems and solving N convex optimization problems to minimize an upper bound on a robust performance objective by using a time-varying state-feedback controller for each subsystem. Simulations examples were considered to illustrate the application of the proposed method. (C) 2011 Elsevier Ltd. All rights reserved.
Keyword:
Distributed model predictive control
Robust control
Linear matrix inequalities
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Robust output feedback model predictive control using off-line linear matrix inequalities基于离线线性矩阵不等式的鲁棒输出反馈模型预测控制
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