Model Based Fuzzy Control with Affine T-s Delayed Models Applied to Nonlinear Systems

This paper mainly investigates fuzzy control with affine T-S delayed models, which can be applied to some nonlinear systems. Motivated from performing the linearization process associated with distinct operating points for nonlinear systems, an affine T-S fuzzy model with delayed state is addressed. The overall control then can be performed by the fuzzy inference mechanism, in which the consequent parts are represented by the locally linear affine subsystems with delayed state. Sufficient stability conditions for the unforced T-S affine models with delayed state are first derived. By involving the parallel distributed compensator (PDC), design conditions for the resulting closed-loop systems are further investigated. Since all the proposed criteria are formulated by the linear matrix inequalities (LMIs), we thus can perform the stability analysis or the PDC synthesis via current LMI solvers. A nonlinear numerical example and an applicable physical model with TCP/RED flowing control mechanism are given to demonstrate the validity and effectiveness of the proposed approach.