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Adaptive control of nonlinear dynamic systems usingthetas;-adaptive neural networks

机译:非线性动态系统使用&Thetas的自适应控制; - 一种神经网络

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The adaptive control of dynamic systems with nonlinear parametrization is considered. An algorithm based on a neural network, similar to the TANN algorithm proposed in Annaswamy and Yu (1996), is suggested for adjusting the control parameters. The adaptive controller is shown to lead to stability of the closed-loop system. How the neural network is trained off-line in order to lead to closed-loop stability is described in detail. The resulting improvement in performance using the neural algorithm over the extended Kalman filter algorithm is demonstrated through simulation studies
机译:考虑了具有非线性参数化的动态系统的自适应控制。一种基于神经网络的算法,类似于Annaswamy和Yu(1996)中提出的Tann算法,用于调整控制参数。示出自适应控制器导致闭环系统的稳定性。神经网络如何离线训练,以便在详细描述闭环稳定性。通过仿真研究证明了在扩展卡尔曼滤波器算法上使用神经算法的性能改善

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