针对四旋翼飞行器姿态控制中采用自抗扰控制技术的控制器参数过多、整定时难以获得一组最优解的问题, 提出了一种变权重与杂交的粒子群优化算法。该算法主要由两部分组成: 第一, 根据迭代过程中粒子群中粒子与全局最优粒子间的距离大小动态改变惯性权重, 并设置系数控制其对惯性权重的影响程度; 第二, 引入杂交进化, 在指定迭代次数内, 若粒子群全局最优值连续未变, 则对指定数量的粒子进行杂交, 增加粒子多样性, 避免陷入局部最优。通过Matlab/Simulink搭建四旋翼飞行器模型并仿真, 其结果表明, 该优化算法对ADRC控制器参数的整定是有效的, 能使四旋翼飞行器的控制品质得到保证和优化, 提升设计效率。

Because the Active Disturbance Rejection Control (ADRC) technology adopts too many controller parameters in the attitude control of quadrotor aircraft, it is difficult to obtain a set of optimal solutions. To solve the problem, a PSO algorithm with variable-weight hybridization is proposed. The algorithm is mainly composed of two parts. First, according to the distance between the particles in the particle group and the global optimal particle in the iterative process, the inertia weight is dynamically adjusted, and the coefficient is set to control the degree of influence on the inertia weight. Second, the hybridization is introduced. Within a specified number of iterations, if the global optimal value of the particle group does not change continuously, the specified number of particles are hybridized to increase the particle diversity and avoid falling into local optimum. The quadrotor model is built and simulated by Matlab/Simulink. The results show that the optimization algorithm is effective for ADRC controller parameter setting, which can ensure the control quality of the quadrotor and improve the design efficiency.