| Full text | |
| Author(s): |
Zabala, Yeison Andres
[1]
;
Costa, V, Oswaldo Luiz
Total Authors: 2
|
| Affiliation: | [1] V, Univ Sao Paulo, Dept Engn Telecomunicacoes & Controle, Escola Politecn, BR-05508010 Sao Paulo - Brazil
Total Affiliations: 1
|
| Document type: | Journal article |
| Source: | IEEE Transactions on Automatic Control; v. 65, n. 3, p. 1211-1217, MAR 2020. |
| Web of Science Citations: | 1 |
| Abstract | |
This paper considers the quadratic control problem of discrete-time Markov jump linear systems with constraints on the norm of the state and control variables. We assume that the Markov chain parameter is not available, and instead, there is a detector, which emits signals providing information on this parameter. It is desired to derive a feedback linear control using the information provided by this detector in order to stochastically stabilize the closed-loop system, satisfy the constraints whenever the initial conditions belong to an invariant set, and minimize an upper bound for the quadratic cost. We show that a linear matrix inequality (LMI) optimization problem can be formulated in order to obtain a solution for this problem. Two other related problems, one for minimizing the guaranteed quadratic cost considering fixed initial conditions and the other for maximizing an estimate of the domain of an invariant set, can also be formulated using our LMI approach. This paper is concluded with some numerical simulations. (AU) | |
| FAPESP's process: | 14/50851-0 - INCT 2014: National Institute of Science and Technology for Cooperative Autonomous Systems Applied in Security and Environment |
| Grantee: | Marco Henrique Terra |
| Support Opportunities: | Research Projects - Thematic Grants |