Robust Cascade PID-based Controller Design for Brushless DC Motor using Antlion Optimization Algorithm
Brushless DC (BLDC) motors are widely utilized in various fields, including high-speed drives, artificial heart pumps, and electric vehicles, due to their superior torque, compact size, and enhanced efficiency. However, it is very difficult to obtain satisfactory control
performance for BLDC motors using conventional PID
controller, because of the difficulty in tuning the proper PID parameters.
In this paper, an optimal cascade PID controller is designed for
controlling the BLDC motor. The proposed cascade controller consist of an inner loop and an outer loop, each responsible for different aspects of the control process. The inner loop handles fast dynamics, namely current control, while the outer loop deals with slower dynamics, as speed control. This separation allows each loop to be optimized individually, resulting in improved overall system performance and stability. By quickly responding to disturbances in the inner loop, cascade controllers can effectively overcome oscillations and enhance the stability of the motor. Additionally, cascade controllers can better handle non-linearities and parameter variations, leading to more accurate and reliable control of the output. However, tuning PID controller gains is crucial for achieving optimal performance and stability in control systems, and metaheuristic algorithms offer significant benefits by efficiently searching for the best gain values, even in complex and high-dimensional parameter spaces. The proposed cascade PID controller’s gains are optimized using the Antlion Optimization (ALO) algorithm, a modern metaheuristic algorithm known for its effectiveness in constrained problems and diverse search spaces. This optimization enhances the controller’s robustness against disturbances, particularly supply voltage variations. To validate the system’s performance, Hardware-in-Loop (HIL) Typhon technology is employed, allowing real-time testing of the BDCM and controller under various conditions. This ensures the reliability and effectiveness of the system before actual implementation.