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RESEARCH PRODUCT
Extended Horizon Adaptive Model Algorithmic Control
Krzysztof J. Latawiecsubject
Model predictive controlAdaptive controlControl theoryComputer scienceRobustness (computer science)Covariance matrixAdaptive systemSystem identificationEstimatorGeneral MedicineRobust controlCovarianceLeast squaresdescription
Abstract A new, original, robust adaptive control strategy termed Extended Horizon Adaptive Model Algorithmic Control is presented. In EHAMAC, a new, combined, ’single-loop’/’cascade’ adaptive least-squares parameter estimator is coupled with a new, simple but powerful Extended Horizon Model Algorithmic Control so that open-loop stable non-minimum phase systems can be effectively controlled in the time-varying environment. In the new, cascade structure of the ALS estimator, the covariance windup and blowup are totally eliminated. Moreover, the sacramental square-root update of the covariance matrix is no longer needed On the other hand, employing EHMAC facilitates robustness design so that controller parameters can be effectively auto-tuned.
year | journal | country | edition | language |
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1997-07-01 | IFAC Proceedings Volumes |