Performance Analysis of optimization techniques and Intelligence Techniques for speed control of DC motor

Aim of This paper Performance Analysis of controllers such as PID controller, fuzzy logic controller and G.A based PID for speed control of DC motor. Simulation results have established that the use of Self Tuned fuzzy logic and GA-PID results in a good dynamic behaviour of the DC motor, a great speed tracking with lowest overshoot, gives better performance and high forcefulness than those obtained by use of the other controller. The DC motor is broadly used in many applications like steel mills, electric trains, cranes and much more. In this paper a separately excited dc motor using MATLAB modelling has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed The principle point of this paper is to dissect the execution of Optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for speed control of DC motor and list their points of interest over the traditional tuning strategies. The output speed error and its derivative as feedback damping signals. Through this simulation the performance of the GA-PID is compared with that of the Fuzzy Logic controller. The GA-PID optimized but FLC gives better performance in terms of delay time, peak time, steady state error.