Particle Swarm Optimisation Algorithm Based Multi-Controller Parameter Adjustment Methods

The controllers in the multi-motor servo system are position-loop PID controller, speed-loop PID controller and current-loop proportional controller, and the controller parameters determine the steady state performance and dynamic performance of the system response. In this paper, the particle swarm algorithm is used to optimize the parameters of the position loop speed loop PID controller in the multi-motor servo system at the same time, and the simulation experiments are carried out with the optimized PID parameters on the step input signals and sinusoidal input signals. The simulation experiments show that the PID parameters optimized by particle swarm optimization have good tracking performance for both step and sinusoidal input signals. The superiority of particle swarm algorithm is verified by 100 generations of population optimization process, which has excellent ability to find the global optimum value.