OPTIMIZATION OF PID CONTROLLER USING PSO ALGORITHM FOR A GIMBAL SYSTEM

Gimbal systems are widely used in applications such as surveillance cameras, satellites, sensors, drones, and spy planes, which has prompted many scientific studies aimed at improving these systems. As a result, gimbal technology has become an exciting research area focused on enhancing stability, reliability, and smooth control. The PID controller is the most commonly used in industrial control loops because of its simple structure, robustness, and ease of implementation. However, precise tuning of the PID is crucial, as conventional methods have some limitations. This has led to the use of new technique such as particles swarm optimization (PSO) to tuning Kp, Ki, and Kd parameters of PID controller in order to achieve smoother control. This paper focuses on the control technique of the Particle Swarm Optimization (PSO) algorithm for tuning the PID controller and compares the results with traditional methods, such as the Ziegler-Nichols (ZN) method. The approach is applied to determine the optimal parameters (Kp, Ki, Kd) for a proportional-derivative (PD) controller. The optimal values obtained were Kp=10.4, Ki=0, and Kd=0.80, which significantly improve the performance and quality of the output signal. When compared to traditional methods, these values minimize steady-state errors, resulting in an ISE of 0.05602, an ITAE of 0.0862, a settling time (t_s) of 0.281 seconds, and a rise time (t_r) of 0.093 seconds, while effectively eliminating overshoot. The goal of this optimization is to achieve maximum system stability.