Application of Improved Particle Swarm Optimization Algorithm in Converter Differential Pressure

Abstract

In view of the characteristics of nonlinear, time varying and large disturbance of converter pressure difference control object. The control scheme of the converter differential pressure is analyzed. An improved particle swarm optimization algorithm (ISPO) is used to optimize the PID parameters of the converter differential pressure controller, which enhances the adaptive ability of the PID controller. At the same time, the inertia weight w adopts a nonlinear decreasing strategy and increases the extreme value perturbation operator. The evolutionary stagnation step t is set as the threshold value, and the individual and global extremum of the PSO are randomly perturbed by the extreme value perturbation operator, so that the system is always in an unbalanced state, In this way, the PSO algorithm is prevented from falling into a stagnant state, a new search path and domain are generated, the optimization of the three parameters of the PID is accelerated, and the probability of obtaining the optimal solution is greatly increased, and the optimization of the three parameters of the PID is accelerated. Finally, the simulation analysis and engineering application of matlab show that compared with the conventional PID control, the improved differential pressure of the converter controlled by the improved particle swarm optimization algorithm has the advantages of small overshoot, short adjustment time, good stability and strong antiinterference ability.