无人机参数优化自抗扰编队保持控制器设计

针对无人机编队飞行中的队形保持问题,采用结合粒子群算法的自抗扰控制技术对控制器进行设计,使响应过程具有良好的动态品质和较小的稳态误差。建立三维空间内基于相对误差的无人机编队飞行模型,并在此基础上设计了跟踪微分器、扩展状态观测器和非线性状态反馈自抗扰控制器,采用粒子群算法对控制器中部分参数进行优化整定。仿真结果表明,设计的结合粒子群算法的改进自抗扰控制器具有良好的控制性能,能以较高的精度实现无人机编队保持任务。

Design of parameter optimization active disturbance rejection controller for UAV formation

In order to solve the problem of formation maintenance in UAV formation flight, this paper proposed the anti-disturbance control technology combined with particle swarm optimization algorithm, so that the response process would have good dynamic quality and small static error. A UAV formation flying model was established based on relative error in a three-dimensional space. On this basis, the tracking differentiator, the extended state observer and the nonlinear state feedback controller were designed. At the same time, the particle swarm algorithm was used to optimize and tune some parameters in the controller. The simulation results show that the improved auto disturbance rejection controller designed by combining the particle swarm algorithm has good control performance and can complete the mission of maintaining the UAV formation with high precision.