期刊
AUTOMATICA
卷 49, 期 8, 页码 2435-2439出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2013.03.010
关键词
Linear-quadratic regulators; Stochastic control; Constraints
Here we consider a state-constrained stochastic linear-quadratic control problem. This problem has linear dynamics and a quadratic cost, and states are required to satisfy a probabilistic constraint. In this paper, the joint probabilistic constraint in the model is converted to a conservative deterministic constraint using a multi-dimensional Chebyshev bound. A maximum volume inscribed ellipsoid problem is solved to obtain this probability bound. Using the probability bound, we develop a recursive state feedback control algorithm for a special class of state-constrained stochastic linear-quadratic regulator (LQR). The performance of this approach is explored in a numerical example. (C) 2013 Elsevier Ltd. All rights reserved.
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