首页> 外文会议>Advances in Neural Networks - ISNN 2007 pt.1; Lecture Notes in Computer Science; 4491 >Adaptive Control for a Class of Nonlinear Time-Delay Systems Using RBF Neural Networks
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Adaptive Control for a Class of Nonlinear Time-Delay Systems Using RBF Neural Networks

机译:基于RBF神经网络的一类非线性时滞系统的自适应控制

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In this paper, adaptive neural network control is proposed for a class of strict-feedback nonlinear time-delay systems. Unknown smooth function vectors and unknown time-delay functions are approximated by two neural networks, respectively, such that the requirement on the unknown time-delay functions is relaxed. In addition, the proposed systematic backstepping design method has been proven to be able to guarantee semiglobally uniformly ultimately bounded of closed loop signals, and the output of the system has been proven to converge to a small neighborhood of the desired trajectory. Finally, simulation result is presented to demonstrate the effectiveness of the approach.
机译:针对一类严格反馈的非线性时滞系统,提出了一种自适应神经网络控制方法。未知的平滑函数向量和未知的时延函数分别通过两个神经网络进行近似,从而放宽了对未知时延函数的要求。另外,已证明所提出的系统的反推设计方法能够保证半全局均匀地最终限制闭环信号,并且已证明系统的输出收敛到期望轨迹的小邻域。最后,仿真结果表明了该方法的有效性。

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