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Design of robust fuzzy iterative learning control for nonlinear batch processes

Authors :
Wei Zou
Yanxia Shen
Lei Wang
Source :
Mathematical Biosciences and Engineering, Vol 20, Iss 11, Pp 20274-20294 (2023)
Publication Year :
2023
Publisher :
AIMS Press, 2023.

Abstract

In this paper, a two-dimensional (2D) composite fuzzy iterative learning control (ILC) scheme for nonlinear batch processes is proposed. By employing the local-sector nonlinearity method, the nonlinear batch process is represented by a 2D uncertain T-S fuzzy model with non-repetitive disturbances. Then, the feedback control is integrated with the ILC scheme to be investigated under the constructed model. Sufficient conditions for robust asymptotic stability and 2D $ H_\infty $ performance requirements of the resulting closed-loop fuzzy system are established based on Lyapunov functions and some matrix transformation techniques. Furthermore, the corresponding controller gains can be derived from a set of linear matrix inequalities (LMIs). Finally, simulations on the three-tank system and the highly nonlinear continuous stirred tank reactor (CSTR) are carried out to prove the feasibility and efficiency of the proposed approach.

Details

Language :
English
ISSN :
15510018
Volume :
20
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Mathematical Biosciences and Engineering
Publication Type :
Academic Journal
Accession number :
edsdoj.445aee0634b1988bc768b0d491f78
Document Type :
article
Full Text :
https://doi.org/10.3934/mbe.2023897?viewType=HTML