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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhiyuan Ren Krogh, B.H. |
| Copyright Year | 2001 |
| Description | Author affiliation: Dept. of Electr. & Comput. Eng., Carnegie Mellon Univ., Pittsburgh, PA, USA (Zhiyuan Ren) |
| Abstract | This paper presents a switching control strategy for multi-mode Markov decision processes. The system to be controlled is modeled as a finite-state controlled Markov chain with a mode that evolves stochastically. Although the system state is observable, the mode is only partially observable in the sense that we know the system mode only when it is in a given set of observable modes. Given a set of controllers for the system, we consider the problem of determining a switching rule that selects the controller to be applied each time the system mode is observable. The objective is to minimize a long-term average cost from the system while satisfying bounds on the long-term average of other given performance measures. We assume the multi-mode model parameters are unknown a priori, so an adaptive switching rule is required. Algorithms are presented for computing approximations to the optimal switching rule based on estimating the model parameters online. The approach is illustrated for an example of dynamic power management of hard disk drives in computer systems. |
| Sponsorship | IEEE Control Syst. Soc |
| Starting Page | 2095 |
| Ending Page | 2101 |
| File Size | 583484 |
| Page Count | 7 |
| File Format | |
| ISBN | 0780370619 |
| DOI | 10.1109/CDC.2001.980561 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-12-04 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Control systems Power system modeling Energy management Power system management Optimal control Control system synthesis Hard disks Application software Costs Parameter estimation |
| Content Type | Text |
| Resource Type | Article |
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