基于多模型仿真器的非线性方形MIMO系统多变量自适应神经控制

2014 IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD14) Pub Date : 2014-05-01 DOI:10.1109/SSD.2014.6808769

N. Bahri, A. Atig, R. Abdennour, F. Druaux, D. Lefebvre

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引用次数: 6

摘要

本文介绍了基于多模型仿真器的非线性方形MIMO系统的多变量自适应神经控制。多模型方法是一种有趣的替代方法，也是建模和仿真复杂过程的强大工具。本文研究了非耦合多模型非线性多输入多输出系统的辨识问题。通过一个多变量自适应神经控制方案，说明了该多模型在系统仿真中的有效性。在这种情况下，既不需要初始化参数，也不需要在线适配。通过数值仿真验证了所提出的多模型仿真器和控制设计的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Multivariable adaptive neural control based on multimodel emulator for nonlinear square MIMO systems

This work describes multivariable adaptive neural control based on multimodel emulator for nonlinear square MIMO systems. Multimodel approach is an interesting alternative and a powerful tool for modelling and emulating complex processes. This paper deals with the identification of nonlinear MIMO systems employing an uncoupled multimodel. Efficiency of this multimodel for systems emulation is illustrated in a multivariable adaptive neural control schemes. Neither initialization parameter and nor online adaptation are required in this case. The effectiveness of the proposed multimodel emulator and the control design are shown through numerical simulations.

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来源期刊

2014 IEEE 11th International Multi-Conference on Systems, Signals & Devices (SSD14)

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