Evaluating PID Controller Tuning via Metaheuristics: A Comparative Case Study

Proportional–Integral–Derivative (PID) controllers have been the industry standard for regulating processes, yet traditional tuning methods, such as the Ziegler-Nichols formula, often fail to consistently achieve satisfactory results, typically requiring extensive manual adjustment by engineers. This study evaluates and compares the performance of Particle Swarm Optimization (PSO) and Bayesian Optimization Algorithm (BOA) for tuning PID controller parameters across several transfer functions. Each algorithm is tested through multiple iterations on a range of simulated system to assess their effectiveness and consistency. The computational results showed that the PSO overcame the BOA.