基于BFO-FPA参数寻优无人直升机轨迹跟踪自抗扰控制

Unmanned helicopter trajectory tracking active disturbance rejection control based on BFO-FPA parameter optimization

为解决小型无人直升机轨迹跟踪控制受系统数学模型精度、自身低成本微机电系统(MEMS)姿态测量误差及飞行环境干扰的内外扰动影响问题,设计了一种基于线性/非线性混合自抗扰控制(ADRC-LADRC)的无人直升机轨迹跟踪控制器,并提出了一种基于细菌觅食优化-花授粉算法(BFO-FPA)的控制器参数整定方法,提高了BFO算法的收敛速度,增强了FPA算法的全局搜索能力。最后,通过ALIGN无人直升机锁尾螺旋爬升飞行试验,验证了BFO-FPA算法参数寻优后自抗扰轨迹跟踪控制器能有效克服无人直升机受内外扰动的影响,提高了控制器轨迹跟踪精度和鲁棒性。

In order to solve the problem that the trajectory tracking control of small unmanned helicopters is affected by internal and external disturbances such as the accuracy of system mathematical model,the attitude measurement error caused by the low-cost MEMS and the interference of flight environment,a linear/nonlinear hybrid active disturbance rejection control(ADRC-LADRC)method was designed for the unmanned helicopter trajectory tracking controller.Furthermore,a controller parameter tuning method based on bacterial foraging optimization-flower pollination algorithm(BFO-FPA)was proposed,which improved the convergence speed of BFO algorithm and enhanced the global search capability of FPA algorithm.Finally,with the ALIGN unmanned helicopter′s tail-locking spiral climb flight test,it was verified that the optimized active-disturbance rejection trajectory tracking controller based on BFO-FPA algorithm can effectively overcome the influence of internal and external disturbances on the unmanned helicopter and improve the trajectory tracking accuracy and robustness of controller.