Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88747
Title: Stochastic Channel Allocation for Nonlinear Systems with Markovian Packet Dropout
Authors: Long, Yushen
Liu, Shuai
Xie, Lihua
Chen, Jie
Keywords: Markovian Packet Dropout
Model Predictive Control
Issue Date: 2018
Source: Long, Y., Liu, S., Xie, L., & Chen, J. (2018). Stochastic Channel Allocation for Nonlinear Systems with Markovian Packet Dropout. Journal of Systems Science and Complexity, 31(1), 22-37.
Series/Report no.: Journal of Systems Science and Complexity
Abstract: This paper addresses a channel scheduling problem for group of dynamically decoupled nonlinear subsystems with actuators connected through digital communication channels and controlled by a centralized controller. Due to the limited communication capacity, only one channel can be activated and hence there is only one pair of sensor and actuator can communicate with the controller at each time instant. In addition, the communication channels are not reliable so Markovian packed dropout is introduced. A predictive control framework is adopted for controller/scheduler co-design to alleviate the performance loss caused by the limited communication capacity. Instead of sending a single control value, the controller sends a sequence of predicted control values to a selected actuator so that there are control input candidates which can be fed to the subsystem when the actuator does not communicate with the controller. A stochastic algorithm is proposed to schedule the usage of the communication medium and sufficient conditions on stochastic stability are given under some mild assumptions.
URI: https://hdl.handle.net/10356/88747
http://hdl.handle.net/10220/44703
ISSN: 1009-6124
DOI: 10.1007/s11424-018-7295-5
Schools: School of Electrical and Electronic Engineering 
Rights: © 2018 The Editorial Office of JSSC & Springer-Verlag GmbH. This paper was published in Journal of Systems Science and Complexity and is made available as an electronic reprint (preprint) with permission of The Editorial Office of JSSC & Springer-Verlag GmbH. The published version is available at: [http://dx.doi.org/10.1007/s11424-018-7295-5]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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