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A multi-model algorithm for parameter estimation of time-varying nonlinear systems
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DOI：10.1016/S0005-1098(97)00203-3.png)
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摘要
En 中文
We present a new on-line multi-model algorithm for parameter estimation of time-varying nonlinear systems. The time variation is captured by assuming that the system parameters change according to a Markovian mechanism. The algorithm postulates a finite number of possible values of the system parameter and computes recursively the credit function of each parameter value, according to its predictive accuracy. A convergence analysis of the algorithm is presented which indicates that the algorithm estimates correctly the parameter value in the time intervals between source switchings. This conclusion is corroborated by numerical experiments. (C) 1998 Elsevier Science Ltd. All rights reserved.
Keyword:
parameter estimation
system identification
nonlinear systems
multiple models
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