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首页> 外文期刊>Journal of Aeronautics, Astronautics and Aviation, A >Application Artificial Intelligence Control System for UAV Landing Gear
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Application Artificial Intelligence Control System for UAV Landing Gear

机译:无人机起落架应用人工智能控制系统

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摘要

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.
机译:本文开发了应用人工智能智能控制系统,即用于多输入多输出(MIMO)无人机起落架的自适应小波神经网络(WNN)控制(AWNNC)算法。该AWNC包括WNN控制器和强大的补偿器。 WNN控制器是用于模拟理想控制器的主体跟踪控制器;基于梯度下降法,利用导出的自适应律对WNN的参数进行在线调整。鲁棒的补偿器设计用于消除理想控制器和WNN控制器之间的近似误差。鲁棒的补偿器设计用于消除理想控制器和WNN控制器之间的逼近误差,因此可以实现闭环系统的渐近稳定性。最后,执行无人机起落架以验证所提出的控制方案的有效性。仿真结果证明,人工智能AWNNC可以实现良好的跟踪性能,液压控制系统无任何颤动现象。

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