Research on attitude control strategy of unmanned helicopter based on hybrid particle swarm optimization algorithm. Issue 1 (1st June 2022) - Liu, Zhiqiang; Ye, Xi; Qian, Tonghui; Yu, Linwen
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°.