Soft computing optimisation study of fuzzy parametric uncertain system for real time process control

This paper deals with analysis and design of optimal robust controller for fuzzy parametric uncertain system using soft computing techniques. Fuzzy system is used to handle the uncertainty in the system. The response of fuzzy systems depends on tuning of fuzzy system parameters. Optimisation in designing of fuzzy membership function improves system response. These optimisation algorithms may have their own advantages and limitations. The proposed methodology uses different evolutionary algorithms to optimise the fuzzy membership function. A comparative study is done for modern non-traditional optimisation algorithms in improving the controller response. An optimal control design is used to obtain the control law. The system is converted into state space controllable canonical form with the α-cut property of fuzzy. Kharitonov theorem is used for fuzzy polynomial and stability analysis is done by using the Lyapunov-Popov method. The proposed method is applied to a real time process control.