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Design of robust fuzzy iterative learning control for nonlinear batch processes
- 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