Adaptive position control of a cart moved by DC motor using Grey Wolf Optimizer Algorithm
Recently, the importance of DC motors becomes from its Function and reliability. Those are two important factors that modern mechanisms, processes and products require to success. So DC motor control technology has a very important part to play at origin of machinery design evolution. Its flexibility, efficiency, power, speed and position will have a flow on effect throughout the machine. Our paper presents an investigation of a positioning control system for a DC motor (with Position-Velocity controller) using a Grey Wolf Optimizer algorithm. The parameters of the used conventional PV controller are tuned by GWO to improve the system performance of the DC motor system. The GWO simulates the realistic performance of the leadership hierarchy and hunting mechanism of grey wolves. There are four types of grey wolves which are delta, beta, alpha and omega. These four types can be used for representing and simulating the leadership hierarchy. In order to complete the GWO process, three main procedures of hunting are implemented, searching for prey then pursuing or keep tracking of prey and finally attacking prey. The GWO method is used for a DC motor to avoid the load disturbance problem and its bad effect on the system performance. The simulating results showed the improvement efficiency of the system performance when using GWO.