Design Of ADRC For Unmanned Surface Vehicle Heading Based On Immune Particle Swarm Optimization

Abstract

Aiming at the uncertainty of external disturbance and internal parameters of unmanned surface vehicle during navigation, based on the mathematical model of unmanned surface vehicle response, an extended state observer is designed to estimate the ‘total disturbance’ and complete the design of active disturbance rejection control law. For the difficulty of parameter tuning of active disturbance rejection control, the immune particle swarm optimization algorithm is combined with active disturbance rejection control to optimize the parameters of active disturbance rejection control. The simulation results of heading control show that the active disturbance rejection control with optimized parameters has faster rise time and stronger disturbance rejection ability.