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Adaptive NN control for a class of discrete-time nonlinear systems based on input-output model

机译：基于输入输出模型的一类离散非线性系统的自适应神经网络控制

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摘要

A direct adaptive control structure, inverse controller based on input-output model, is studied for a class of SISO discrete-time nonlinear systems in this paper. The developed controller and adaptation algorithm are very simple to implement. The closed-loop system has been proven to be semi-globally uniformly ultimately bounded (SGUUB) if the design parameters are suitably chosen under certain requirement. An arbitrarily small tracking error can be achieved if the size of neural networks is chosen large enough. Simulation studies verify the effectiveness of the newly designed schemes and the theoretical discussion.

机译：针对一类SISO离散时间非线性系统，研究了一种基于输入输出模型的直接自适应控制结构逆控制器。开发的控制器和自适应算法很容易实现。闭环系统已被证明是半全局一致最终有界（SGUUB）如果设计参数被适当地在一定的要求选择。如果将神经网络的大小选择得足够大，则可以实现任意小的跟踪误差。仿真研究验证了新设计方案和理论讨论的有效性。

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《》|2002年|p.3246-3251|共6页
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Ge; S.S.; Li; G.Y.; Lee; T.H.;
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中图分类无线电电子学、电信技术;
关键词
neural nets; discrete time systems; nonlinear systems; adaptive control; closed loop systems; adaptive NN control; discrete-time nonlinear systems; input-output model; direct adaptive control structure; inverse controller; SISO systems; closed-loop s;

机译：神经网络离散时间系统;非线性系统自适应控制闭环系统;自适应神经网络控制离散时间非线性系统投入产出模型直接自适应控制结构;逆控制器; SISO系统;闭环;

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Adaptive NN control for a class of discrete-time nonlinear systems based on input-output model

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