Research on Cascade Fuzzy PID Control of Quadrotor UAV Based on Genetic Algorithm Optimization
In order to meet the control requirements of low delay and high precision of the flight process of quadrotor UAVs,according to the system characteristics such as strong coupling,multivariate and underdrive,based on certain assumptions and parameter experiments,a nonlinear mathematical model and Euler angle transfer function are established through kinematic and dynamic analysis.Using the efficient global search capability of genetic algorithm,the steady-state error,adjustment time and overshoot are selected to construct the objective function,which realizes the unified optimization of the initial PID parameters,quantization factors and scale factors in the traditional cascade fuzzy attitude PID controller.The traditional PID and genetic algorithms are compared in different scenarios to optimize the PID and the simulation control effectiveness of the algorithm,and some comparison items are verified by real machines,and the results show that the proposed method could effectively improve the stability and responsiveness of the system.
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