Hybrid control of load simulator for unmanned aerial vehicle based on wavelet networks

How to eliminate the surplus torque of a loading system is one of the key problems to design a load simulator. Based on the learning characteristic of neural network and the function approximation ability of the wavelet, a hybrid control based on wavelet networks was proposed. The application results in the unmanned aerial vehicle load simulator show that the proposed controller can effectively eliminate the surplus torque and fairly improve the dynamic loading performances of the loading simulator. In addition, the results show that the proposed controller belongs to the fine robustness for unknown external loading disturbances.