Identification and Fuzzy Controller Design for Nonlinear Uncertain Systems with Input Time-Delay
This paper considers the identification and fuzzy controller design for nonlinear uncertain systems in presence (if unknown input time-delay. Firstly, a time-delay Takagi-Sugeno-Kang (TSK) type fuzzy neural system (TDFN) is proposed to identify a class of nonlinear input time-delay systems. The input-output signals of nonlinear systems are used to identify the system dynamics and unknown time-delay, and then construct the system in the form TSK-fuzzy time-delay model. Each fuzzy rule has a corresponding linear system with an input time-delay as the consequent part. Based on parallel distribution compensation (PDC) approach, the Smith predictor compensation and dominate pole assignment technique are then adopted to design the fuzzy PID controller. Several simulations are shown to demonstrate the effectiveness and control performance of the proposed approach.
time-delay systems smith predictor pid controller nonlinear control tsk type fuzzy model neural networks