Adaptive Discrete-Time Flight Control Using Disturbance Observer and Neural Networks

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Adaptive Discrete-Time Flight Control Using Disturbance Observer and Neural Networks

机译：使用干扰观测器和神经网络的自适应离散飞行控制

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This paper studies the adaptive neural control (ANC)-based tracking problem for discrete-time nonlinear dynamics of an unmanned aerial vehicle subject to system uncertainties, bounded time-varying disturbances, and input saturation by using a discrete-time disturbance observer (DTDO). Based on the approximation approach of neural network, system uncertainties are tackled approximately. To restrain the negative effects of bounded disturbances, a nonlinear DTDO is designed. Then, a backstepping technique-based ANC strategy is proposed by utilizing a constructed auxiliary system and a discrete-time tracking differentiator. The boundness of all signals is proven in the closed-loop system under the discrete-time Lyapunov analysis. Finally, the feasibility of the proposed ANC technique is further specified based on numerical simulation results.

机译：本文通过使用离散时间扰动观测器（DTDO）研究基于自适应神经控制（ANC）的无人飞行器离散时间非线性动力学的跟踪问题，该系统具有系统不确定性，有界时变扰动和输入饱和度。基于神经网络的近似方法，可以近似地解决系统的不确定性。为了限制有界干扰的负面影响，设计了非线性DTDO。然后，利用构造的辅助系统和离散时间跟踪微分器，提出了一种基于反推技术的ANC策略。在离散时间Lyapunov分析下，在闭环系统中证明了所有信号的边界。最后，基于数值模拟结果进一步说明了所提出的ANC技术的可行性。

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《Neural Networks and Learning Systems, IEEE Transactions on》 |2019年第12期|3708-3721|共14页
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Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Jiangsu Peoples R China|Concordia Univ Dept Mech Ind & Aerosp Engn Montreal PQ H3G 1M8 Canada;

Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 211106 Jiangsu Peoples R China;

Concordia Univ Dept Mech Ind & Aerosp Engn Montreal PQ H3G 1M8 Canada;

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正文语种 eng
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关键词
MIMO communication; Uncertainty; Unmanned aerial vehicles; Force; Artificial neural networks; Aerodynamics; Disturbance observers; Backstepping control; disturbance observer (DO); neural network (NN); nonlinear discrete-time systems (NDTSs); unmanned aerial vehicle (UAV);

机译：MIMO通信;不确定;无人机力;人工神经网络;空气动力学干扰观察员;反步控制;干扰观察者（DO）;神经网络（NN）;非线性离散时间系统（NDTS）;无人机（UAV）;

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1. Adaptive Neural Discrete-Time Fractional-Order Control for a UAV System With Prescribed Performance Using Disturbance Observer [J] . Shuyi Shao, Mou Chen IEEE Transactions on Systems, Man, and Cybernetics . 2021,第2期

机译：使用干扰观测器具有规定性能的UAV系统的自适应神经离散时间分数控制
2. Disturbance-Observer-Based Robust Flight Control for Hypersonic Vehicles Using Neural Networks [J] . Mou Chen, Chang-Sheng Jiang, Qing-Xian Wu Advanced Science Letters . 2011,第4a5期

机译：基于神经网络的高超声速飞行器基于扰动观测器的鲁棒飞行控制
3. Composite anti-disturbance control for uncertain Markovian jump systems with actuator saturation based disturbance observer and adaptive neural network [J] . Wei Yunliang, Liu Guo-Ping, Zong Guangdeng, Journal of the Franklin Institute . 2019,第13期

机译：基于执行器饱和的扰动观测器和自适应神经网络的不确定马尔可夫跳跃系统的复合抗干扰控制
4. Disturbance-observer-based control for discrete-time delayed standard neural networks [C] . Hou Linlin, Zong Guangdeng Chinese Control Conference . 2013

机译：基于扰动观察者的离散时间延迟标准神经网络控制
5. Nonlinear adaptive control of discrete-time systems using neural networks and multiple models. [D] . Chen, Lingji. 2001

机译：使用神经网络和多种模型的离散时间系统的非线性自适应控制。
6. Synchronization of a Non-Equilibrium Four-Dimensional Chaotic System Using a Disturbance-Observer-Based Adaptive Terminal Sliding Mode Control Method [O] . Shaojie Wang, Amin Yousefpour, Abdullahi Yusuf, 2020

机译：使用干扰观察者的自适应终端滑动模式控制方法同步非平衡四维混沌系统
7. Neural Networks Approximator Based Robust Adaptive Controller Design of Hypersonic Flight Vehicles Systems Coupled with Stochastic Disturbance and Dynamic Uncertainties [O] . Guoqiang Zhu, Lingfang Sun, Xiuyu Zhang 2017

机译：基于神经网络的基于神经网络的高度扰动和动态不确定因素的高超声速飞行器系统的逼真自适应控制器设计
8. Adaptive Policies for Discrete-Time Stochastic Control Systems with Unknown Disturbance Distribution [R] . Hernandaz-Lerma, O., Marcus, S. I. 1987

机译：具有未知扰动分布的离散随机控制系统的自适应策略

Adaptive Discrete-Time Flight Control Using Disturbance Observer and Neural Networks

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