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基于ELM的一类MIMO仿射非线性系统的鲁棒自适应控制

DOI: 10.13195/j.kzyjc.2014.0999, PP. 1559-1566

Keywords: 鲁棒自适应神经控制,极限学习机,单隐层前馈网络,多输入多输出,仿射非线性系统

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Abstract:

针对一类多输入多输出(MIMO)仿射非线性动态系统,提出一种基于极限学习机(ELM)的鲁棒自适应神经控制方法.ELM随机确定单隐层前馈网络(SLFNs)的隐含层参数,仅需调整网络的输出权值,能以极快的学习速度获得良好的推广性.在所提出的控制方法中,利用ELM逼近系统的未知非线性项,针对ELM网络的权值、逼近误差及外界扰动的未知上界值分别设计参数自适应律,通过Lyapunov稳定性分析可以保证闭环系统所有信号半全局最终一致有界.仿真结果表明了该控制方法的有效性.

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