A new model validity monitoring method for nonlinear recursive identification
نویسندگان
چکیده
In the present study, a new correlation test based model validity monitoring procedure is proposed to online check the quality of nonlinear recursively identified models. The new method provides a simple but effective diagnose of nonlinear recursive models by detecting if the residuals are reduced to uncorrelated noise sequences. In the monitoring procedure, the correlation functions are periodically computed with a specified frequency and a constant data window. The computational time and sensitivity of the correlation tests can be easily modified by adjusting the testing time interval, data length, and maximum lag. A simulated case study is employed to demonstrate the effectiveness and efficiency of the new method.
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