NDLI: Wireless event-driven networked predictive control over internet

Content Provider	IEEE Xplore Digital Library
Author	Wenshan Hu Hong Zhou Qijun Deng
Copyright Year	2012
Description	Author affiliation: Department of Automation, School of Mechanical and Power Engineering, Wuhan University, 430072, China (Wenshan Hu; Hong Zhou; Qijun Deng)
Abstract	In networked control systems, the network uncertainties can degrade the control performance and even result in instability, especially for the Internet-based control system with wireless communication in which the transmission delay could be many times of the sampling period of control systems. NPC (Networked Predictive Control) is an active method to compensate for the effects of network uncertainty. However, control systems need to make long time prediction due to the long transmission distance. Without an accurate mathematical model, the control performance can not be guaranteed. In order to address this problem, a new NPC scheme designed for wireless NPC with long time delay is introduced in this paper. It uses the information of the previous prediction errors to correct the future predictions. A correction algorithm is designed to reduce the predictive errors. To validate the new control schemes, both simulations and experiments have been conducted. The results show that even with “not so” accurate mathematical models, the new schemes can still maintain good control performance in Internet-based NPC with wireless communication.
Starting Page	668
Ending Page	673
File Size	1188010
Page Count	6
File Format	PDF
ISBN	9781467315593
e-ISBN	9781467315609
e-ISBN	9781467315586
DOI	10.1109/CONTROL.2012.6334709
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-03
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless communication Uncertainty Delay effects Predictive models Internet Mathematical model Delay
Content Type	Text
Resource Type	Article

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