Design of robust fuzzy iterative learning control for nonlinear batch processes

Math Biosci Eng. 2023 Nov 7;20(11):20274-20294. doi: 10.3934/mbe.2023897.

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.

Keywords: 2D $ H_\infty $ performance; fuzzy iterative learning control; nonlinear batch processes; robust asymptotic stability; uncertain T-S fuzzy model.