Identification and optimal fractional-order pid controller for a position servo system

Model base design not only changes the way engineers and scientists work by moving development process from labs to computers but also cut down development time and costs. The first step in the modelbased design process is to build a mathematical model in order to simulate and analyze the system behavior. Therefore, a practical system identification algorithm is discussed then successfully implemented on the servo position system. The second step is controller design, in recent years many researchers are interested in the field of fractional-order calculus, particularly in dynamic and control systems design. It allows to describe the dynamic systems more accurate and enhance the controller performance. However fractional order PID controller design became more challenge since it has two more extra parameters than conventional PID controller. In contrast, the recent developments in meta-heuristic algorithms have made the design process of an optimal controller not very complicated. Thus, three different search algorithms, namely genetic algorithms (GA), particle swarm optimization (PSO), and gray wolf optimization (GWO), are employed to find the optimal parameters of both controller, fractional order controller and the special form of fractional order controller, integral order PID controller.