改进人工蜂群算法的四旋翼自抗扰控制参数优化

针对四旋翼自抗扰控制(active disturbance rejection controller, ADRC)参数整定困难，给工程应用带来较大限制的问题，提出一种改进人工蜂群算法的四旋翼ADRC控制器参数优化方法。该算法采用自适应的探索策略，根据选择概率，从5种不同的搜索规则中进行选择，提高种群的多样性和寻优能力。将ADRC控制器中的参数作为蜂群中的种群应用到四旋翼无人机仿真模型中进行迭代寻优，并把风干扰模型作为环境噪声引入系统，测试算法性能。仿真结果表明，改进后的人工蜂群算法得到的控制器参数响应速度更快，稳态误差更小，抗干扰能力更强。

Optimization Parameters of Quadrotor ADRC Based on Improved Artificial Bee Colony Algorithm

To address the problem of difficult parameter setting of quadrotor active disturbance rejection controller (ADRC), which brings large limitation to engineering applications, a quadrotor ADRC controller parameter optimization method based on improved artificial bee colony algorithm is proposed. The algorithm adopts an adaptive exploration strategy to select from five different search rules according to the selection probability to improve the diversity of the population and the ability to find the best. The parameters in the ADRC controller are then applied to the quadrotor UAV simulation model as populations in a bee colony for iterative optimization search, and the wind interference model is introduced into the system as environmental noise to test the algorithm performance. The simulation results show that the improved artificial bee colony algorithm yields controller parameters with faster response, smaller steady-state error, and better anti-interference capability.