Abstract
An adaptive suboptimal control algorithm is proposed for discrete-time stochastic systems with constant but unknown parameters. The linear control law is certainty-equivalent in the sense that it is linear in the estimates of the states and that the feedback gain matrix is calculated using the estimates of the unknown parameters. In this work the control scheme is separated into an adaptive estimator which simultaneously estimates the states and identifies the parameters of the sytem, and a certainty-equivalent controller which makes use of the state and parameter estimates as if they were the true values. For the estimation stage the adaptive state estimator of Ljung (1) is employed and for the control stage the receding horizon concept of Thomas and Barraud (2) is made use of, which is shown to have the desirable property of making the closed-loop stochastic system asymptotically stable
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Reference
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© 1983 D. Reidel Publishing Comapany
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Yaz, E., Istefanopulos, Y. (1983). Adaptive Receding Horizon Controllers for Discrete Stochastic Systems. In: Bucy, R.S., Moura, J.M.F. (eds) Nonlinear Stochastic Problems. NATO ASI Series, vol 104. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-7142-4_16
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DOI: https://doi.org/10.1007/978-94-009-7142-4_16
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