Nonlinear Discrete-Time System Identifications Based on Fuzzy Models: Algorithms and Performance Analyses
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摘要: 讨论使用模糊系统方法辨识非线性离散时间系统时,模糊系统模型的构造、逼近性 质以及模型参数的自适应调整算法.研究了该辨识方案的有关性能,对模糊模型的参数误差 和辨识误差进行了分析,并给出了模糊模型参数的估计值收敛到其真实值所需的持续激励条 件.Abstract: This paper investigates the constructions, the approximation properties, and the parameter tuning algorithms of fuzzy system models in identification of nonlinear discretetime systems with fuzzy system approach. The performance of the identification scheme is analyzed, including the parameter error and prediction error of the fuzzy model. The persistent excitation conditions are established, under which the parameters of the fuzzy system model converge to their true values.
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