Adaptive PID Dc Motor Speed Controller With Parameters Optimized with Hybrid Optimization Strategy

In this paper, an intelligent controller of DC Motor drive is designed using hybrid method of optimization (Genetic Algorithm and Pattern Search Algorithm) for the optimal tuning of proportional-integral-derivative (PID) controller parameters. A proportional–integral–derivative controller (PID controller) is a generic control loop feedback mechanism controller widely used in industrial control system. The parameters of motor, which vary with the operating conditions of the system, are adapted in order to maintain deadbeat response for motor speed. A Hybrid optimization algorithm is employed in order to obtain the controller parameters assuring deadbeat response at each selected load. The DC-Motor PID-HYBRID controller is modeled in MATLAB environment. The response of the developed controllers is compared to that of the controllers whose parameters are tuned using the well-known Ziegler-Nichols method. The developed methodology is more proficient in improving the controller loop response stability, the steady state error, the rising time and overshoot and hence the disturbances do not affect the performances of DC-motor.