Multi-step output feedback predictive control for uncertain discrete-time T–S fuzzy system via event-triggered scheme

Abstract

This paper addresses a synthesis approach of multi-step event-triggered output feedback model predictive control (OFMPC) for uncertain discrete-time Takagi–Sugeno (T–S) fuzzy system with bounded disturbance. An event-triggered scheme, which aims at reducing the redundant signal transmission, is designed to determine whether the current measured output should be released or not. The parameter-dependent output feedback predictive controller is presented by minimizing the upper bound of an infinite horizon quadratic objective function respecting input constraint. Based on this result, an additional optimization problem to tighten the bound of the state error is provided, which is of crucial importance on the control performance. The overall multi-step predictive control approach, which parameterizes the infinite horizon control moves into a sequence of output feedback laws, offers more degrees of freedom for optimization and leads to better control performance with the increase of the switching horizon. Simulation results of a continuous stirred tank reactor (CSTR) system are given to demonstrate the effectiveness of the provided techniques.