Stochastic adaptive control using a modified least squares algorithm |
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Authors: | Kwai Sang Sin Graham C. Goodwin |
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Affiliation: | 1. Department of Electrical Engineering, University of Newcastle, NSW 2308, Australia |
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Abstract: | Recent papers on stochastic adaptive control have established global convergence for algorithms using a stochastic approximation iteration. However, to date, global convergence has not been established for algorithms incorporating a least squares iteration. This paper establishes global convergence for a slightly modified least squares stochastic adaptive control algorithm. It is shown that, with probability one, the algorithm will ensure that the system inputs and outputs are sample mean square bounded and the mean square output tracking error achieves its global minimum possible value for linear feedback control. |
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Keywords: | Adaptive control discrete time systems identification least squares approximation linear systems parameter estimation self-adjusting systems |
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