Gap-Metric-Based Multiple-Model Predictive Control with a Polyhedral Stability Region

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• 作者：Xiangyuan Tao ; Dewen Li ; Yishi Wang ; Ning Li ; Shaoyuan Li
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2015
• 出版时间：November 18, 2015
• 年：2015
• 卷：54
• 期：45
• 页码：11319-11329
• 全文大小：600K
• ISSN：1520-5045

文摘

This paper proposes a gap-metric-based multiple model predictive control (MMPC) method for nonlinear systems with a wide operating range. The gap metric theory, integrated into a neighborhood estimation algorithm, is utilized to partition the whole operating range into subregions corresponding to operating points. A local controller is then designed in each subregion and is composed of a constant feedback control and a receding infinite-horizon control with an estimated polyhedral stable region. To guarantee the global stability of the whole system, we design a novel switching rule activating between local controllers. The simulation study on a continuous stirred-tank reactor (CSTR) is presented to validate the proposed methods.