Speed Control of a DC Motor Using Global Search Optimization Method

Abstract There are two aspect to this study. Firstly a new global search method is introduced which was developed by combining the two well-known global search methods, namely Controlled Random Search (CRS), Global Search Using Brownian Motion. Next, this new method has been applied to design of optimal controller for the speed control of a dc motor. The design has been done for various controller structures (PID, Cascade PID and nonlinear feedback) and their performances are compared with each other. Moreover, the results are also compared with the ones obtained by the application of classical optimal control theory and it is seen that the methodology has some merits.