Parameter Identification and Optimal speed controller design for BLDC motor using the Genetic Algorithm

This paper presents the parameter identification of the brushless direct current (BLDC) motor using the Genetic Algorithm (GA) with the multi-speed range objective function in which the black-box model will be proposed. The unknown coefficients of the model will be identified by the proposed algorithm until the errors between the model and experimental responses are at the minimum. For the model validation, the response from the proposed model will be compared with different speeds used in the objective function to confirm the model accuracy. The resulting system parameters will then be used for the speed controller design. In this paper, the GA is also, however, used for the PID controller design to regulate the motor speed. In the controller design process, the control signal will be set as the constrain in the objective function. The simulation results via Simulink of MATLAB program show that the PID controller from the proposed design can regulate the motor speed with better speed response performance.