Simulation and Research on PID Parameter Tuning Based on Improved Beetle Antennae Search Algorithm

Abstract

The traditional PID parameter tuning method has the problem that it is difficult to achieve optimal performance and even lead to system instability. In order to overcome these problems, an improved Beetle Antennae Search (BAS) algorithm is proposed in this paper. By dynamically adjusting the step size, introducing random disturbance and elite reservation strategy, the global optimization ability and convergence speed of the algorithm are significantly improved. In this study, the improved BAS algorithm is applied to the parameter tuning of PID controller. By defining an objective function that comprehensively considers the performance indexes such as system overshoot, regulation time and steady-state error, the algorithm is used for iterative search to determine the optimal PID parameter combination. The experiment uses MATLAB/Simulink platform for simulation, taking the second-order system as the controlled object, and simulating different system dynamics by changing system parameters. The findings from the experiments indicate that the improved BAS algorithm outperforms traditional methods in terms of convergence speed, optimization outcomes, and stability. With an identical number of iterations, the refined algorithm yields a lower objective function value, reduced overshoot, shortened adjustment duration, and diminished steady-state error. The PID parameter tuning technique, grounded on the improved BAS algorithm presented in this research, not only maintains the simplicity inherent to the conventional BAS algorithm but also markedly boosts its global optimization capability and convergence rate. This offers innovative perspectives and techniques for optimizing industrial control systems.