Optimization of PID control parameters with genetic algorithm plus fuzzy logic in stirred tank heater temperature control process

Abstract

This paper describes a method to determine Proportional Integral Derivative (PID) controller parameter using Genetic Algorithm with the Fuzzy Logic controller of temperature control of Stirred Tank Heater. The system design begins with the search for the transfer function on the Stirred Tank Heater. The fuzzy logic system design is used to find the parameters in the Genetic Algorithm is the probability of crossover and the probability of mutation. This parameter is used to find the value of Kp, Ki, and Kd on the PID controller. Based on the experiment, the control system output response reaches error steady state, and overshoot are smaller when the controller is tuned with Genetic Algorithm plus Fuzzy Logic than Ziegler-Nichols method. But in term rise time and settling time, Ziegler-Nichols method is smaller than Genetic Algorithm plus Fuzzy Logic method.