Time-varying parameter estimation and adaptive Kalman filter in computer aided control application
نویسندگان
چکیده
Estimating the unknown parameter vector of system model is most important problems in identification. Especially cases where system's parameters are time-variable, it observed that estimations obtained using estimator have deviated from actual values, and therefore must be corrected to some extent. In this paper, methods for estimation a modelled with ARX Autoregressive Exogenous Input) considered. After reviewing problems, simulation study has been made on comparing different methods. Corrected (Adaptive) Kalman Filter (CKF) gives results more accurately than Normal (NKF) time varying estimation. Moreover, after an introduction method minimum variance feed-back control, CKF, heating control done computer aided experimental study. CKF ensures kept under by correctly estimating changes over time.
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ژورنال
عنوان ژورنال: Sigma Journal of Engineering and Natural Sciences
سال: 2021
ISSN: ['1304-7205', '1304-7191']
DOI: https://doi.org/10.14744/sigma.2021.00023