Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/85939

Iterative learning fault-tolerant control for batch processes based on T-S fuzzy model

Authors Wang, L.
Yang, J.
Yu, J.
Li, B.
Gao, Furong View this author's profile
Issue Date 2017
Source Huagong Xuebao/CIESC Journal , v. 68, (3), March 2017, p. 1081-1089
Summary Batch processes are not with highly nonlinearity, but also suffer from the actuator failures. Study of the stability of nonlinear batch processes under failure conditions is of great significance. With considering on the actuator gain faults and the highly nonlinearity, a new T-S fuzzy model-based iterative learning fault-tolerant control method is proposed for nonlinear batch process. Firstly, the T-S fuzzy model is employed to represent the nonlinear batch process. Then a 2D compound iterative learning fault-tolerant controller is proposed by exploiting the 2D and repetitive nature of batch processes, and the equivalent 2D Rosser model of the fuzzy model is constructed. Lastly, the sufficient condition guaranteeing the system stable is given through a Lyapunov function method, and the controller gains are designed in terms of linear matrix inequalities (LMIs). Simulation to a highly nonlinear continuous stirred tank reactor (CSTR) demonstrates the feasibility and efficiency of the proposed method. © All Right Reserved.
Subjects
ISSN 0438-1157
Language English
Format Article
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