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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Mukaidani, H. Hua Xu Dragan, V. |
| Copyright Year | 2011 |
| Description | Author affiliation: Institute of Mathematics of the Romanian Academy, P.O.Box 1-764, RO-014700, Romania (Dragan, V.) || Graduate School of Education, Hiroshima University, 1-1-1 Kagamiyama, Higashi-Hiroshima, 739-8524 Japan (Mukaidani, H.) || Graduate School of Business Sciences, The University of Tsukuba, 3-29-1, Otsuka, Bunkyo-ku, Tokyo, 112-0012 Japan (Hua Xu) |
| Abstract | In this paper, we consider three types of infinite-horizon multi-objective decision-making problems for a class of discrete-time linear stochastic systems with state- and disturbance-dependent noise. First, the H2/H∞ control problem with multiple decision makers is considered. Second, in order to improve the transient response, the linear quadratic control under the Pareto solution is investigated. Finally, the soft-constrained stochastic Nash games are formulated in which robustness is attained against disturbance input. The decision strategies for the three types of problem are derived. It is found that the conditions for the existences of these strategies are related to the solutions of cross-coupled stochastic algebraic Riccati equations (CSAREs). We develop some new algorithms based on linear matrix inequality (LMI) to solve the CSAREs. Numerical example is provided to verify the efficiency of the proposed decision strategies. |
| Starting Page | 6388 |
| Ending Page | 6393 |
| File Size | 171986 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781612848006 |
| ISSN | 07431546 |
| e-ISBN | 9781612848013 |
| e-ISBN | 9781612847993 |
| DOI | 10.1109/CDC.2011.6160358 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-12-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Stochastic systems Games Noise Manganese Cost function Riccati equations |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Optimization Control and Systems Engineering Modeling and Simulation |
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