Relaxed Fuzzy Model Predictive Control of Discrete-Time Takagi–Sugeno Systems with Nonlinear Local Models: A New Switching Approach

The problem of fuzzy model predictive control of discrete-time Takagi–Sugeno plants possessing nonlinear local models is ulteriorly investigated via designing a new switching fuzzy model predictive controller. To achieve this goal, some key information of membership functions is updated and integrated into the process of the on-line fuzzy model predictive control design at each instant. Therefore, much conservatism of existing results can be eased and thus the underlying finite horizon cost function index can be further improved than before. Furthermore, some essential comparisons between the recent method in the literature and ours have been implemented for showing the obtained advantage of our given method.