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RESEARCH PRODUCT

Extended Horizon Adaptive Model Algorithmic Control

Krzysztof J. Latawiec

subject

Model predictive controlAdaptive controlControl theoryComputer scienceRobustness (computer science)Covariance matrixAdaptive systemSystem identificationEstimatorGeneral MedicineRobust controlCovarianceLeast squares

description

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.

https://doi.org/10.1016/s1474-6670(17)42864-3