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首页> 外文期刊>IEEE Transactions on Automatic Control >Input-output modeling of nonlinear systems with time-varying linearmodels
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Input-output modeling of nonlinear systems with time-varying linearmodels

机译:具有时变线性模型的非线性系统的输入输出建模

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摘要

Time varying ARMA (autoregressive moving average) and ARMAX (autoregressive moving average with exogenous inputs) models are proposed for input-output modeling of nonlinear deterministic and stochastic systems. The coefficients of these models are estimated by a random walk Kalman filter (RWKF). This method requires no prior assumption on the nature of the model coefficients, and is suitable for real-time implementation since no off-line training is needed. A simulation example illustrates the method. Goodness of performance is judged by the quality of the residuals, histograms, autocorrelation functions and the Kolmogorov-Smirnoff test
机译:提出了时变ARMA(自回归移动平均值)和ARMAX(具有外生输入的自回归移动平均值)模型,用于非线性确定性和随机系统的输入-输出建模。这些模型的系数由随机游走卡尔曼滤波器(RWKF)估计。该方法无需事先假设模型系数的性质,并且由于不需要离线训练,因此适合实时实施。仿真示例说明了该方法。性能的优劣由残差,直方图,自相关函数和Kolmogorov-Smirnoff检验的质量来判断

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