An LMI Method to Robust Iterative Learning Fault-tolerant Guaranteed Cost Control for Batch Processes  

作　　者：王立敏 陈曦 高福荣 

机构地区：[1]Fok Ying Tung Graduate School, Hong Kong University of Science and Technology, Ciear Water Bay, Kowloon, Hong Kong. China [2]College of Sciences, Liaoning Shihua University, Fushun 113001, China [3]Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China [4]Department of Chemical and Biomolecular Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

出　　处：《Chinese Journal of Chemical Engineering》2013年第4期401-411,共11页中国化学工程学报（英文版）

基　　金：Supported in part by NSFC/RGC joint Research Scheme （N-HKUST639/09）, the National Natural Science Foundation of China （61104058, 61273101）, Guangzhou Scientific and Technological Project （2012J5100032）, Nansha district independent innovation project （201103003）, China Postdoctoral Science Foundation （2012M511367, 2012M511368）, and Doctor Scientific Research Foundation of Liaoning Province （20121046）.

摘　　要：Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller (ILRGCC). A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities (LMIs), and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.Based on an equivalent two-dimensional Fornasini-Marchsini model for a batch process in industry, a closed-loop robust iterative learning fault-tolerant guaranteed cost control scheme is proposed for batch processes with actuator failures. This paper introduces relevant concepts of the fault-tolerant guaranteed cost control and formulates the robust iterative learning reliable guaranteed cost controller （ILRGCC）. A significant advantage is that the proposed ILRGCC design method can be used for on-line optimization against batch-to-batch process uncertainties to realize robust tracking of set-point trajectory in time and batch-to-batch sequences. For the convenience of implementation, only measured output errors of current and previous cycles are used to design a synthetic controller for iterative learning control, consisting of dynamic output feedback plus feed-forward control. The proposed controller can not only guarantee the closed-loop convergency along time and cycle sequences but also satisfy the H∞ performance level and a cost function with upper bounds for all admissible uncertainties and any actuator failures. Sufficient conditions for the controller solution are derived in terms of linear matrix inequalities （LMIs）, and design procedures, which formulate a convex optimization problem with LMI constraints, are presented. An example of injection molding is given to illustrate the effectiveness and advantages of the ILRGCC design approach.

关 键 词：two-dimensional Fornasini-Marchsini model batch process iterative learning control linear matrix inequality fault-tolerant guaranteed cost control 

分 类 号：TP273.22[自动化与计算机技术—检测技术与自动化装置] TP13[自动化与计算机技术—控制科学与工程]