一类非线性系统的辨识算法

Lianming Sun, Yuanming Ding, Yujin Yang
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引用次数: 0

摘要

考虑了非线性系统的局部模型网络辨识方法,该方法适用于非线性过程,其中非线性元素之后是线性动力学。局部模型选择为线性模型或简单的面向块的非线性模型,其阶数由近似精度和模型简单性两方面的准则函数确定。每个局部模型的权重随当前工艺状态的工作点而变化,并通过一些简单的参数估计算法来估计局部模型的参数。该算法可以在非线性信息很少的情况下工作,并且易于在实际系统中实现。并将其应用于具有饱和和间隙的过程,验证了该算法的有效性。
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Identification algorithm for a class of nonlinear systems
Nonlinear system identification based on local model networks is considered for the nonlinear process where a nonlinear element is followed by linear dynamics. The local model is chosen as a linear model, or a simple block oriented nonlinear model, whose orders are determined through a criterion function with respect to both the approximation accuracy and model simplicity. The weight of every local model varies with the operating point of the present process state, and the parameters of local models are estimated through some simple parameter estimation algorithms. The algorithm can work even under the situation where little information on nonlinearity is available, and it can be implemented easily in practical systems. Moreover, its application to the processes with saturation and backlash is investigated to show the effective of the proposed algorithm.
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