Adaptive Tabu Search Optimization Applied on Fuzzy Logic DC Motor Speed Control

Abstract

In this work , two different types of controllers has been used, the first one is presents the application of fuzzy logic for DC motor speed control using Adaptive Tabu Search optimization and the second is Ziegler-Nlchols methods for PID controller tuning. A comparative study was done for two type of controllers, namely adaptive tabu search based tuning of fuzzy controller (Fuzzy-ATS) and Ziegler– Nichols methods for PID controller tuning to control of nonlinear drive. The work main objective is to obtain best performance of the system in both transient and steady state response represented by, minimum settling time and minimum overshoot under various conditions such as : change in load , change in speed and change in both load and speed of the motor . General Terms The intelligent optimization technique of Adaptive Tabu Search (ATS) is proposed to tune the fuzzy controller parameters to get optimal results of close loop of Fuzzy ATS Controllers while, Ziegler– Nichols methods for tuning PID controller is represented as a point comparison . The system is simulated using Matlab/Simulink GUI environment and the results is discussed. The result shows that Fuzzy ATS controllers perform well by providing the best transient and steady state DC motor speed response.