基于径向基函数网络的非线性离散时间系统的自适应控制
Adaptive Control of Nonlinear Discrete-Time Systems Using Radial Basis Function Networks
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摘要: 对于一类离散时间的非线性系统x(k+1)=f(x(k))+u(k)+d(k),当系统中的非 线性函数f(x(k))满足线性增长条件时,首先证明了{x(k)}落入一紧集中,然后根据高斯径 向基函数网络的逼近性质,给出了自适应控制器的设计方法.利用李亚普诺夫稳定性理论,证 明了控制算法是全局稳定的,跟踪误差收敛于零的某一领域中.Abstract: For a class of nonlinear discrete-time systems x(k+l)=f(x(k))+u(k)+ d(k), when nonlinear function f(x (k)) satisfies linear growth condition, we first prove that for all k, {x(k)} falls into a compact set, then an adaptive controller is proposed based on the approximation capability of radial basis function networks. According to the Lyapunov stability theory, the algorithm is proved to be globally stable, the tracking error converges to a neighborhood of zero.
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Key words:
- Adaptive control /
- radial basis function networks /
- stability
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