Metaheuristic Algorithms to Determine PID Controller Parameters for Mobile Robots

Numerous technological systems are being controlled by newly developed intelligent systems. In contrast, the PID (Proportional-Integral-Derivative) controller is a rapid low-level control method frequently employed in control engineering tasks. Various tuning techniques from classical control theory have been utilized to determine the PID controller gains under specific operating conditions. This paper provides a comprehensive survey of modern strategies for adjusting PID parameters using metaheuristic algorithms to enhance control system performance. Challenges in different scenarios of parameter adjustment, including specific models, are considered. The methods are thoroughly classified and evaluated, focusing on popular algorithms such as GA, PSO, FLC, among others. These methods are analyzed, simulated, and assessed in particular cases. MATLAB simulation results indicate that metaheuristic algorithms significantly reduce errors and improve stability compared to other methods. Finally, the paper discusses proposals and future research directions for PID parameter optimization.