A New Recursive Identiication Algorithm for Singularity Free Adaptive Control
نویسنده
چکیده
Reportedly, guaranteeing the controllability of the estimated system is a crucial problem in adaptive control. In this paper, we introduce a least squares-based identiication algorithm for stochastic SISO systems, which secures the uniform con-trollability of the estimated system and presents closed-loop identiication properties similar to those of the least squares algorithm. The proposed algorithm is recursive and, therefore, easily implementable. Its use, however, is connned to cases in which the parameter uncertainly is highly structured.
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تاریخ انتشار 2007