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Output feedback control for constrained pure-feedback systems: A non-recursive and transformational observer based approach

机译:受约束纯反馈系统的输出反馈控制:基于非递归和变换观测的方法

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In this paper we investigate the control problem of uncertain pure-feedback systems under time-varying output constraints using output information only. By making use of the salient cascade properties of pure-feedback systems as well as a novel scaling function, we convert the constrained system into a normal form without constraints. Then by using only one single neural network (NN) unit for nonlinear approximation and one high-gain observer for transformed state estimation, an adaptive NN output feedback control scheme is constructed. Different from existing results in the literature, our method exhibits the following features: (1) achieving semi-global stable control with only output feedback without imposing any additional restrictive condition; (2) avoiding the recursive design procedures required by some typical approaches such as backstepping; and (3) recovering the steady-state tracking performance under the state feedback. Besides, all the signals in the closed-loop are bounded and the output constraints are never violated. The effectiveness and flexibility of the developed method is demonstrated through control design and simulation on the non-trivial aircraft short-period dynamics. (C) 2019 Published by Elsevier Ltd.
机译:在本文中,我们仅使用输出信息调查不确定纯反馈系统的控制问题。通过利用纯反馈系统的突出级联属性以及新颖的缩放功能,我们将约束系统转换为不受限制的正常形式。然后,通过仅使用一个用于非线性近似的单个神经网络(NN)单元和用于变换状态估计的一个高增益观测器,构造了自适应NN输出反馈控制方案。不同于文献中的现有结果,我们的方法表现出以下特征:(1)实现半全局稳定控制,只有输出反馈,而不会施加任何额外的限制性条件; (2)避免诸如Backstepping等一些典型方法所需的递归设计程序; (3)在国家反馈下恢复稳态跟踪性能。此外,闭环中的所有信号都被界限,输出约束永远不会违反。通过对非普通飞机短周期动态的控制设计和仿真来证明开发方法的有效性和灵活性。 (c)2019年由elestvier有限公司出版

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