Robust distributed model predictive control for systems of parallel structure within process networks

作     者：Zhang, Shuzhan Zhao, Dongya Spurgeo, Sarah K. 

作者机构：China Univ Petr East China Coll New Energy Dept Chem Equipment & Control Engn Qingdao Shandong Peoples R China UCL Dept Elect & Elect Engn Torrington Pl London England 

出 版 物：《JOURNAL OF PROCESS CONTROL》 (工艺过程控制杂志)

年 卷 期：2019年第82卷

页      面：70-90页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 0817[工学-化学工程与技术] 08[工学] 070105[理学-运筹学与控制论] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0701[理学-数学] 071101[理学-系统理论] 

基　　金：National Natural Science Foundation of China [61973315, 61473312] Changjiang Scholar Project 

主　　题：Parallel system Competitive coupling Competitive constraint Robust distributed model predictive control Linear matrix inequality 

摘      要：The parallel structure is one of the basic system architectures found in process networks. In order to achieve robust control of complex process networks, it is necessary to formulate control strategies that specifically accommodate the characteristics of such parallel systems. In this paper, the competitive coupling and competitive constraints in parallel systems are initially defined. A novel robust distributed model predictive control algorithm is then developed for such parallel systems which deals explicitly with competitive couplings, competitive constraints and uncertainties. The Lyapunov Method is used for the theoretical analysis which produces tractable linear matrix inequalities (LMI). Two simulation studies and an experimental trial are provided to validate the effectiveness of the proposed approach. These consider control of 40 user and 100 user gas boiler heating systems as well as control of two continuous stirred tank reactors (CSTRs) which are connected in parallel. (C) 2019 Elsevier Ltd. All rights reserved.