标题:Iterative Learning Fault-Tolerant Control for Networked Batch Processes with Multirate Sampling and Quantization Effects
作者:Gao, Ming; Sheng, Li; Zhou, Donghua; Gao, Furong
通讯作者:Gao, Furong
作者机构:[Gao, Ming; Sheng, Li] China Univ Petr East China, Coll Informat & Control Engn, Qingdao 266580, Peoples R China.; [Zhou, Donghua] Shandong Univ Sci 更多
会议名称:20-Year Anniversary Symposium on Adsorption of Metals by Geomedia III held at the 251st National Spring Meeting of the American-Chemical-Society (ACS)
会议日期:MAR 13-17, 2016
来源:INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
出版年:2017
卷:56
期:9
页码:2515-2525
DOI:10.1021/acs.iecr.6b04609
摘要:The fault-tolerant control problem is investigated for a class of networked batch processes with actuator faults and external disturbances. A two-dimensional Fornasini-Marchesini (2D-FM) system with multirate sampling and quantization effects is introduced to model the networked batch processes, which may reflect the reality more closely. The aim of this paper is to design a dynamic output feedback controller such that the closed-loop system can achieve fault tolerance with the effect of actuator faults and satisfy the H8 performance constraint for unknown external disturbances. By employing a combination of the Lyapunov stability analysis theory, lifting technique, and logarithmic quantization method, a networked iterative learning fault-tolerant control (NILFTC) scheme is first proposed, and some sufficient conditions are established for the existence of the desired dynamic output feedback controller. Finally, an example is exploited to illustrate the effectiveness of the developed method.
收录类别:CPCI-S;EI;SCIE
WOS核心被引频次:2
资源类型:会议论文;期刊论文
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