A Penalized Identiication Criterion for Securing Controllability in Adaptive Control
نویسندگان
چکیده
Reportedly, standard identiication algorithms do not guarantee the controllability of the estimated system. In this paper, a penalized least squares (PLS) identiication criterion is proposed to overcome this diiculty. The criterion is shown to provide estimated systems which exhibit an uniform controllability property through time. Moreover, the Lai and Wei upper bound for the least squares estimation error ((1], Theorem 1) is still valid for PLS. This ensures a safe use of the proposed method in adaptive control applications. The eeectiveness of the method is illustrated by a general adaptive stability result valid for PLS-based certainty-equivalent adaptive control schemes.
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