PID parameter optimization method based on PSO-SOA fusion algorithm

Abstract

The invention discloses a PID parameter optimization method based on a PSO-SOA fusion algorithm; a particle swarm algorithm is fused with a crowd search algorithm, and when the target values of the particles tend to be consistent, that is, when the fitness value Fitness (i) of the particles is greater than or equal to the average fitness value Favg, the optimal solution is sought by the crowd search algorithm with strong global searching capability, and the convergence precision is improved; and when the target values of the particles are relatively dispersed, that is, when the Fitness (i) isless than Favg, the particle swarm optimization is adopted to carry out relatively high local development, so that the group is rapidly converged, and the convergence speed is increased. Based on thePSO-SOA fusion algorithm, excellent global searching capability and local searching capability are achieved, and a brand-new idea is provided for setting the PID parameters; in addition, the problemsthat a standard particle swarm algorithm is prone to being caught in local optimum and the crowd searching algorithm is low in convergence speed are solved; and the control precision is improved, theresponse speed of the system is increased, the performance of the control system is enhanced, the adjusting process of the control system is more rapid and stable, the overshoot amount is small, and the steady-state error is low.

Description

technical field

[0001] The invention belongs to the technical field of swarm intelligence algorithms, and in particular relates to a PID parameter optimization method based on a PSO-SOA fusion algorithm. Background technique

[0002] PID control is the earliest classic control strategy and one of the most widely used strategies in industrial process control. PID control has been widely used in chemical industry, electric power, machinery and other industrial control processes due to its simple structure, mature technology, good robustness, and easy adjustment in practical applications. Even if people have accumulated a lot of experience in setting PID parameters, for some nonlinear and large-lag control systems, the controller parameters cannot be adjusted to the best state, and the control system cannot achieve good control effects, which affects the safety and security of industrial production processes. stability.

[0003] In order to improve the performance of PID cont...

Images