Optimal PID Controller Parameters Tuning for a 3D Satellite Simulator Based on Particle Swarm Optimization Algorithm

Due to its effectiveness and practicality, the proportional-integral-derivative (PID) controller remains a cornerstone of industrial control systems. The precise tuning of controller parameters significantly impacts system dynamics, influencing key performance metrics such as rise time, settling time, overshoot, stability, and steady-state error. While conventional methods effectively tune PID parameters in linear systems, they are inadequate for nonlinear processes due to the complexity of dynamic equations. This study proposes applying the particle swarm optimization (PSO) algorithm for tuning PID controller parameters in a three-degree-of-freedom satellite attitude simulator. The simulator incorporates reaction wheel actuators for attitude control, providing a robust platform for implementing control algorithms and optimizing onboard computational processes. The PSO-based optimization algorithm was executed for various performance criterion functions, demonstrating advantages such as rapid convergence to optimal values and straightforward implementation in nonlinear control systems. PID parameters derived from the conventional Ziegler-Nichols method were also applied to the simulator to benchmark the nonlinear optimization performance. Experimental results comparing different PID parameter sets were analyzed based on time response characteristics during a predefined maneuver. The comparative analysis identified the optimal PID parameters, which were subsequently implemented for enhanced simulator performance.