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首页> 外文期刊>International Journal of Adaptive Control and Signal Processing >Robust exponential stability and H_∞ control for switched neutral-type neural networks
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Robust exponential stability and H_∞ control for switched neutral-type neural networks

机译:切换中立型神经网络的鲁棒指数稳定性和H_∞控制

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摘要

In this paper, we consider the problem of robust exponential stability for a class of uncertain switched delayed neutral-type neural networks with an H_∞ performance level γ > 0. Further, the result is extended to design an H_∞ control law to ensure the robust exponential stabilization of the closed-loop neural networks about its equilibrium point with the guaranteed H_∞ performance level γ, for all norm bounded parameter uncertainties. On the basis of a new set of Lyapunov-Krasovskii functional, linear matrix inequality technique, and average dwell time approach, a set of novel sufficient conditions is derived for the existence of H_∞ performance and as well as existence of H_∞ control problem. The obtained results are derived in the form of convex optimization problems, which can be solved easily by the standard Matlab control toolbox. Numerical examples with simulation results are provided to illustrate the effectiveness of the proposed method.
机译:在本文中,我们考虑了H_∞性能水平γ> 0的一类不确定切换时滞中立型神经网络的鲁棒指数稳定性问题。此外,将结果推广到设计H_∞控制律以确保对于所有范数有界参数不确定性,闭环神经网络在其平衡点附近具有鲁棒指数稳定,且具有保证的H_∞性能水平γ。基于一组新的Lyapunov-Krasovskii泛函,线性矩阵不等式技术和平均停留时间方法,为存在H_∞性能以及存在H_∞控制问题导出了一组新颖的充分条件。获得的结果以凸优化问题的形式导出,可以通过标准Matlab控制工具箱轻松解决。数值算例和仿真结果表明了该方法的有效性。

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