Abstract

This paper presents an improved particle swarm optimization (PSO) algorithm to optimize the coefficients of the proportional integral derivative (PID) controller for trajectory tracking accuracy problems. Nonlinear adaptive methods are adopted on the inertia weight to built a balance between the local and global search areas, asynchronous change strategies are introduced into the learning coefficients to rationally use individual and group experience, an elite mutation method is designed to mutate the global best position in each iteration. Basic PSO (BPSO-PID) and Ziegler-Nichols PID controller (ZN-PID) are implemented with step, sinusoidal and slope references on a co-simulation platform. The simulation results illustrate that high accuracy and fast convergence can be obtained based on the improved PSO algorithm PID controller (IPSO-PID). Experimental results demonstrated that the IPSO-PID method can achieve the highest tracking accuracy, compared with the BPSO-PID method, this method can improve the tracking accuracy by 37.14% and 50.32%, respectively.

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