Application Artificial Intelligence Control System for UAV Landing Gear

Abstract

This paper develops application artificial intelligence smart control system, the adaptive wavelet neural network (WNN) control (AWNNC) algorithm for multiple-input-multiple-output (MIMO) UAV landing gear. This AWNC comprises a WNN controller and a robust compensator. The WNN controller is a principal tracking controller utilized to mimic an ideal controller; and the parameters of WNN are on-line tuned by the derived adaptation laws based on the gradient descent method. The robust compensator is designed to dispel the approximation error between the ideal controller and the WNN controller. The robust compensator is designed to dispel the approximation error between the ideal controller and the WNN controller, so the asymptotic stability of the closed-loop system can be achieved. Finally, an UAV landing gear is performed to verify the effectiveness of the proposed control scheme. Simulation results verify that artificial intelligence AWNNC can achieve favorable tracking performance, hydraulic pressure control system without any chattering phenomenon.