针对无人机在不确定外扰和强耦合等姿态控制问题，用欧拉法进行建模并线性化。结构上，由于姿态变化对位置的控制效果影响较大，所以姿态层采用串级分控，由线性自抗扰控制器(linear active disturbance rejection controller，LADRC)和模糊控制器以平滑函数进行自切换控制。其中针对线性自抗扰控制参数整定困难，提出一种改进的蜣螂优化算法，首先利用混沌映射增加种群的覆盖率;其次通过加权系数法将多目标的优化问题转化为单目标问题，并在种群寻优过程中加入高斯扰动利于跳出局部最优值。通过仿真结果表明，所提出的控制方法对飞行器有良好的鲁棒性和快速性。
Quadrotor self-switching control based on improved dung beetle optimization algorithm
For the unmanned aerial vehicle attitude control problems such as uncertain external disturbance and strong coupling,the Euler method is used to model and linearized.Structurally,since attitude changes have a large impact on the control effect of position,the attitude layer is controlled by a series-level sub-control with a linear self-anti-disturbance controller and a fuzzy controller with a smooth function for self-switching control.Among them,an improved dung beetle optimization algorithm is proposed for the difficulty of linear self-turbulence control parameter rectification,which firstly increases the coverage of the population by using chaotic mapping;secondly,the multi-objective optimization problem is transformed into a single-objective problem by the weighted coefficient method,and the Gaussian perturbation is added in the population search process to facilitate the jumping out of the local optimum.The simulation results show that the proposed control method has good robustness and fast performance for the vehicle.
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