Research on attitude control strategy of unmanned helicopter based on hybrid particle swarm optimization algorithm

Abstract

For the unmanned helicopter attitude control problem, an optimal control strategy based on hybrid particle swarm optimization (PSO) algorithm has been proposed. Firstly, a coupled dynamics model of the system has been established based on the structural characteristics of the unmanned helicopter system; secondly, a gain scheduling control method has been adopted to select multiple system stable operating points with real-time error as the scheduling variable, and a gain scheduling attitude controller has been designed; further, the inertia weights and learning factors are dynamically adjusted on the basis of the traditional PSO algorithm, and a hybrid PSO algorithm has been proposed for unmanned helicopter attitude control; finally, the improved controller has been compared and verified by the semi-physical. The experimental results show that the improved algorithm improves the attitude control effect and anti-interference capability of the unmanned helicopter, resulting in a reduction of the adjustment time by about 3.8s and the maximum steady-state amplitude by about 0.154°.