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Model-predictive control of discrete hybrid stochastic automata

Bemporad, Alberto and Di Cairano, Stefano Model-predictive control of discrete hybrid stochastic automata. IEEE Transactions on Automatic Control , 56 (6). 1307 -1321. ISSN 0018-9286 (2011)

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This paper focuses on optimal and receding horizon control of a class of hybrid dynamical systems, called Discrete Hybrid Stochastic Automata (DHSA), whose discrete-state transitions depend on both deterministic and stochastic events. A finite-time optimal control approach “optimistically”; determines the trajectory that provides the best tradeoff between tracking performance and the probability of the trajectory to actually execute, under possible chance constraints. The approach is also robustified, less optimistically, to ensure that the system satisfies a set of constraints for all possible realizations of the stochastic events, or alternatively for those having enough probability to realize. Sufficient conditions for asymptotic convergence in probability are given for the receding-horizon implementation of the optimal control solution. The effectiveness of the suggested stochastic hybrid control techniques is shown on a case study in supply chain management.

Item Type: Article
Identification Number: 10.1109/TAC.2010.2084810
Projects: “Advanced control methodologies for hybrid dynamical systems” (PRIN’2005)
Funders: This work was supported in part by the European Commission under the HYCON Network of Excellence, contract number FP6-IST- 511368, and by the Italian Ministry for Education, University and Research
Uncontrolled Keywords: asymptotic convergence; discrete hybrid stochastic automata; discrete-state transition; finite-time optimal control solution; horizon control; model-predictive control; probability; receding-horizon implementation; stochastic event; stochastic hybrid dynamical control technique; supply chain management; tracking performance; asymptotic stability; optimal control; predictive control; stochastic automata; supply chain management
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TJ Mechanical engineering and machinery
Research Area: Computer Science and Applications
Depositing User: Professor Alberto Bemporad
Date Deposited: 28 Jul 2011 09:52
Last Modified: 04 Aug 2011 07:29
URI: http://eprints.imtlucca.it/id/eprint/728

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