Optimization of dependently controlled jump rates of JLQG problem |
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Authors: | Yankai Xu Xi Chen |
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Affiliation: | Tsinghua National Laboratory for Information Science and Technology, Department of Automation, Tsinghua University, Beijing, 100084, China |
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Abstract: | The Jump Linear Quadratic Gaussian (JLQG) model is well studied due to its wide applications. However, JLQG with controlled jump rates are rarely researched, while the existing studies usually impose an assumption that jump rates are independent and separately controlled. In practical systems, their jump rates may not be independent of each other. In this paper, we consider a continuous‐time JLQG model with dependently controlled jump rates and formulate it as a two‐level control problem. The low‐level problem is a standard JLQG problem, thus we focus on solution of high‐level problem. We propose a Markov decision process‐based approach to calculate performance gradient with respect to jump rates control variable and develop a gradient‐based optimization algorithm. We present an application of manufacturing system to illustrate the main results of this paper. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society |
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Keywords: | Jump linear quadratic Markov decision processes performance potential coupled Riccati equation |
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