多旋翼无人机飞行串联模糊免疫智能控制系统设计

Design of Fuzzy Immune Intelligent Control System for Multi rotor Unmanned Aerial Vehicle Flight Series

摘要:

多旋翼无人机采用分布式电机布局,各旋翼的推力特性存在差异,进而产生电机转速响应延迟、桨叶气动效率不一致以及机械结构微小偏差,导致三轴推力耦合特性非线性化,影响控制精度。为此,设计多旋翼无人机飞行串联模糊免疫智能控制系统。在处理器与传感器模块中,设计系统飞行控制的硬件架构,实现多旋翼无人机飞行导航数据采集与处理。在导航模块中,基于多旋翼无人机飞行导航数据,通过融合导航算法实现多旋翼无人机飞行导航。在串联模糊免疫飞行控制模块中,设计模糊控制器与免疫控制器串联的PID飞行控制器。针对高速飞行时的非线性气动耦合问题,应用改进遗传算法实施串联PID飞行控制器的控制参数优化,补偿气动干扰引起的微小偏差,实现多旋翼无人机的飞行智能控制。测试结果表明,设计系统的姿态角响应曲线、偏航角响应曲线、高度稳定响应曲线均与期望曲线较为贴近,说明其飞行控制准确性较强。

Abstract:

Multi rotor unmanned aerial vehicles adopt a distributed motor layout, and there are differences in the thrust characteristics of each rotor, resulting in delayed motor speed response, inconsistent blade aerodynamic efficiency, and small mechanical structural deviations, leading to nonlinear three-axis thrust coupling characteristics and affecting control accuracy. To this end, a multi rotor unmanned aerial vehicle flight series fuzzy immune intelligent control system is designed. Design the hardware architecture for system flight control in the processor and sensor modules to achieve data acquisition and processing for multi rotor unmanned aerial vehicle flight navigation. In the navigation module, based on the flight navigation data of multi rotor unmanned aerial vehicles, the fusion navigation algorithm is used to achieve multi rotor unmanned aerial vehicle flight navigation. Design a PID flight controller in series with a fuzzy controller and an immune controller in the fuzzy immune flight control module. Aiming at the nonlinear aerodynamic coupling problem during high-speed flight, an improved genetic algorithm is applied to optimize the control parameters of a series PID flight controller, compensate for small deviations caused by aerodynamic interference, and achieve intelligent flight control of multi rotor unmanned aerial vehicles. The test results show that the attitude angle response curve, yaw angle response curve, and altitude stability response curve of the designed system are all close to the expected curve, indicating that its flight control accuracy is strong.