Genetic fuzzy approach for controlling parameters varying processes

A control scheme (GFPID) is proposed to control processes that have varying parameters. These processes are very common in nature. Usually, traditional controllers are not suitable for these processes. The new control scheme combines the traditional PID controller with genetic algorithm and fuzzy logic to solve this problem. The optimum PID settings to minimize integral square error will be obtained by genetic algorithms. A fuzzy compensator is designed and implemented to compensate for process parameter variation. Simulation results show the power and simplicity of the proposed scheme compared to the famous method of least square identijication and controller parameter adaptation.