Parameter Optimization of PID Controller Based on Improved Sine-SOA Algorithm

Abstract

Aiming at the problem that the traditional PID controller was not ideal, the parameters could not be adjusted to the best state, and the control system could not achieve good control effect, an improved seagull optimization algorithm (SOA) based on improved Sine chaotic mapping was proposed to optimize the parameters of PID controller. Sine mapping strategy was adopted to make the initial seagull population evenly distributed in the search space, to improve the shortcomings of the seagull optimization algorithm, such as low solution accuracy, slow convergence speed and easy to fall into premature convergence, and improve the convergence speed and convergence accuracy of the algorithm. Eight standard test functions were tested, and the improved gull optimization algorithm was compared with the unimproved gull algorithm, particle swarm optimization algorithm (PSO), beetle antennae search algorithm (BAS), particle swarm optimization -beetle antennae search algorithm (PSO-BAS) and the seeker optimization algorithm (TSOA), to verify that the improved gull optimization algorithm has better optimization effect. The improved algorithm is applied to a second-order system and double closed-loop DC motor speed regulation system to optimize the parameters of PID controller. The results show that the algorithm has high precision, simple principle, better convergence precision and faster convergence speed.