Abstract

Based on the relationship between parameter speed \( v_{\hbox{max} } \) and inertia factor \( \omega \) in the particle swarm optimization (PSO) algorithm, the improved PSO algorithm that is time-varying nonlinear trigonometric function to control PSO algorithm parameters is proposed to prevent the particles fall into local optimum, and the improved PSO algorithm is used to optimize parameters of PID controller which is used in course control for underactuated surface vessels (USV). Two different PSO algorithms for optimizing parameters of PID controller are compared in this paper, and the results of simulation experiments show that, according to dynamic characteristics changes of USV, the controller which used improved PSO algorithm can optimize the adaptive parameters well and automatically, and has a high tracking speed, small overshoot and strong immunity etc.

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