基于遗传算法优化的四旋翼控制系统研究

为提高多自由度、非线性的四旋翼无人机模型控制系统的系统响应与控制效果，提出一种基于遗传算法优化的模糊PID控制策略。将整个控制系统分解为外环位置控制器和内环姿态控制器2部分，对四旋翼无人机系统进行建模仿真。由仿真分析结果得知，当滚转角度分别为35°、45°和65°时，通过遗传算法优化的模糊PID控制相对于模糊PID控制的角度误差分别降低2.58°、3.09°和3.78°；X轴误差分别降低了0.759、0.658和0.593 m；Y轴误差分别降低了0.157、0.228和0.195 m；Z轴误差分别降低了0.169、0.237和0.514 m。结果表明：该策略保证了整机的稳定性，使整机的控制系统能达到更好的控制效果，保证了四旋翼无人机具有更好的性能。

Research on Quadrotor Control System Based on Genetic Algorithm Optimization

In order to improve the system response and control effect of the multi-degree-of-freedom and nonlinear quadrotor UAV model control system, a fuzzy PID control strategy based on genetic algorithm optimization is proposed. The whole control system is divided into two parts: the outer loop position controller and the inner loop attitude controller, and the quadrotor UAV system is modeled and simulated. The simulation results show that when the roll angle is 35°, 45° and 65 °, the angle error of the fuzzy PID control optimized by genetic algorithm is reduced by 2. 58°, 3.09° and 3°. 78° compared with the fuzzy PID control, and the X axis error is reduced by 0. 759 m, 0.658 m and 0. 593 m, respectively; The Y-axis error is reduced by 0. 157 m, 0.228 m and 0. 195 m, and the Z-axis error is reduced by 0. 169 m, 0.237 m and 0. 514 m, respectively. The results show that the strategy ensures the stability of the whole aircraft, makes the control system of the whole aircraft achieve better control effect, and ensures the four-rotor UAV has better performance.