Abstract:
Due to their better reliabilities and low costs, nowadays, DC motors are widely used in industrial applications, robot manipulators, and home appliances. There are several types of applications where the load on the DC motor varies over a speed range. These applications demand speed control accuracy and excellent dynamic responses. So, it is vital to introduce a controller to control the speed and transient behavior of a DC motor in the desired manner. In this study, for the enhancement of dynamic response, various DC motor controllers have been simulated. At first, the DC motor parameters are selected and four optimized controllers: Ziegler-Nichols (ZN) method based PID controller, Genetic Algorithm (GA), Flower Pollination Algorithm (FPA) and Modified Flower Pollination Algorithm (MFPA) are designed and simulated in order to control the angular speed and dynamic response of the shaft of a DC motor actuator. Ziegler-Nichols (ZN) sustained oscillation method provided better tuning parameters than the Ziegler-Nichols 1st method. Here, the Genetic Algorithm (GA) provides 7.558 times better rise time, 16.07 times better settling time and 1.48 times better overshoot than the Ziegler-Nichols (ZN) sustained oscillation method based conventional PID controller. The Flower Pollination Algorithm (FPA) provides 7.593 times better rise time, 13.55 times better settling time and 1.41 times better overshoot than Ziegler-Nichols (ZN) sustained oscillation method. Flower Pollination Algorithm provides 1.0046 times better rise time than Genetic Algorithm (GA) based controller. Modified Flower Pollination Algorithm (MFPA) produces 2.2 times better overshoot than the Genetic Algorithm (GA) with acceptable rise and settling time. Modified Flower Pollination Algorithm (MFPA) produces 2.23 times better overshoot and 1.1 times better settling time than the Flower Pollination Algorithm (FPA) based controller. The response of the actuator for each controller is ascertained and compared applying a step input that simulated transient response of the motor. The performance analysis shows that the Modified Flower Pollination Algorithm is adequate for the wheel steering task, which requires precision and associated with transient response properties. It seems reasonable to conclude that the proposed design criteria are effective and satisfactory.
