2D Fuzzy Constrained Fault-Tolerant Predictive Control of Nonlinear Batch Processes

Abstract

Concerning actuator gain faults and strong system nonlinearity in batch processes, a design method of a kind of 2D fuzzy constrained model fault-tolerant predictive controller is proposed. Firstly, introduce two errors: state error and output error, after that the original system model is converted into a 2D Roesser fault model. Meanwhile, the design of iterative learning fault tolerant control under constraints has been transformed into the determination of the constrained update law. Subsequently, real-time on-line design of the fuzzy fault-tolerant update law that ensures the closed-loop system robustly asymptotic stability is presented by taking the appearance of linear matrix inequalities (LMIs) with constraint subject to the designed infinite optimization performance index and Lyapunov stability theory. Finally, taking a three-tank case as an example to compare with the 1D of the method proposed in this paper, the comparison results illustrated the 2D method of this paper has better control effects.