Networked PID control system modeling and simulation using Markov chain
Paper
Paper/Presentation Title | Networked PID control system modeling and simulation using Markov chain |
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Presentation Type | Paper |
Authors | Teng, Lanzhi (Author) and Wen, Peng (Author) |
Journal or Proceedings Title | Proceedings of the 2007 IEEE International Conference on Integration Technology |
Number of Pages | 4 |
Year | 2007 |
Place of Publication | Shenzhen, China |
ISBN | 1424410924 |
Conference/Event | 2007 IEEE International Conference on Integration Technology |
Event Details | 2007 IEEE International Conference on Integration Technology Event Date 20 to end of 24 Mar 2007 Event Location Shenzhen, China |
Abstract | [Abstract]: This paper presents a new model for a Networked PID Control System. In this model a Markov chain is included to represent the unreliable link of the shared networks. In this study we identify the minimum measurement information involved in the PID control system and build it up as an embedded Markov chain. This converts a networked PID control system into a jump control system. This jump control system is evaluated in simulation and the results agree with our analysis. |
Keywords | PID, networked control system, packet drop, Markov chain |
ANZSRC Field of Research 2020 | 400799. Control engineering, mechatronics and robotics not elsewhere classified |
400899. Electrical engineering not elsewhere classified | |
Public Notes | © 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Byline Affiliations | Faculty of Engineering and Surveying |
Department of Electrical, Electronic and Computer Engineering |
https://research.usq.edu.au/item/9y511/networked-pid-control-system-modeling-and-simulation-using-markov-chain
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