Linear quadratic control for sampled-data systems with stochastic delays
説明
We study optimal control for sampled-data systems with stochastic delays. Assuming that the delays can be modeled by a Markov chain and can be measured by controllers, we design a control law that minimizes an infinite-horizon continuous-time quadratic cost function. The resulting optimal control law can be efficiently computed offline by the iteration of a certain Riccati difference equation. We also obtain sufficient conditions in terms of linear matrix inequalities for stochastic stabilizability and detectability, which are used for the optimal controller design.
収録刊行物
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- 2017 American Control Conference (ACC)
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2017 American Control Conference (ACC) 1978-1983, 2017-05-01
IEEE