A fast model identification method for networked control system

Most control strategies for networked control system (NCS) assume that system model is known as ‘a priori’, which are however impractical in many industrial applications. To obtain a suitable model for networked control, this paper concentrates on model identification under the networked control env...

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Vydané v:	Applied mathematics and computation Ročník 205; číslo 2; s. 658 - 667
Hlavní autori:	Fei, Minrui, Du, Dajun, Li, Kang
Médium:	Journal Article Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier Inc 15.11.2008 Elsevier
Predmet:	Approximations and expansions Cubic spline Exact sciences and technology Fast recursive algorithm Mathematical analysis Mathematics Network-induced delay Networked control system Numerical analysis Numerical analysis. Scientific computation Numerical approximation Sciences and techniques of general use Networked control system Network-induced delay Fast recursive algorithm Cubic spline Numerical approximation Interpolation ARMA model Numerical analysis Applied mathematics Control system Fast algorithm Recursive algorithm
ISSN:	0096-3003, 1873-5649
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Abstract	Most control strategies for networked control system (NCS) assume that system model is known as ‘a priori’, which are however impractical in many industrial applications. To obtain a suitable model for networked control, this paper concentrates on model identification under the networked control environment. A networked identification scheme is proposed here, and nondeterministic factors such as network-induced delay, data packet out-of-order, and data packet loss between the sensor and identifier as well as the identifier and the actuator are considered. A discard-packet strategy is first developed to deal with network nondeterministic factors from the sensor to the identifier, and a cubic spline interpolation is used to compensate lost data. Actuator buffers are then introduced for actuator nodes to handle network nondeterministic factors between the identifier and the actuator. Finally, a fast recursive algorithm is used both to select the model structure and to estimate the unknown system parameters. Experiments on ARMA model identification and NARMAX model identification are performed respectively under different network loads. Simulation results show that the proposed networked identification scheme can effectively overcome the impact of various network-induced nondeterministic factors and significantly improve model identification performance.
AbstractList	Most control strategies for networked control system (NCS) assume that system model is known as ‘a priori’, which are however impractical in many industrial applications. To obtain a suitable model for networked control, this paper concentrates on model identification under the networked control environment. A networked identification scheme is proposed here, and nondeterministic factors such as network-induced delay, data packet out-of-order, and data packet loss between the sensor and identifier as well as the identifier and the actuator are considered. A discard-packet strategy is first developed to deal with network nondeterministic factors from the sensor to the identifier, and a cubic spline interpolation is used to compensate lost data. Actuator buffers are then introduced for actuator nodes to handle network nondeterministic factors between the identifier and the actuator. Finally, a fast recursive algorithm is used both to select the model structure and to estimate the unknown system parameters. Experiments on ARMA model identification and NARMAX model identification are performed respectively under different network loads. Simulation results show that the proposed networked identification scheme can effectively overcome the impact of various network-induced nondeterministic factors and significantly improve model identification performance.
Author	Du, Dajun Fei, Minrui Li, Kang
Author_xml	– sequence: 1 givenname: Minrui surname: Fei fullname: Fei, Minrui email: mrfei@staff.shu.edu.cn organization: School of Mechatronical Engineering and Automation, Shanghai University, Shanghai 200072, China – sequence: 2 givenname: Dajun surname: Du fullname: Du, Dajun email: ddj559@163.com organization: School of Mechatronical Engineering and Automation, Shanghai University, Shanghai 200072, China – sequence: 3 givenname: Kang surname: Li fullname: Li, Kang email: k.li@ee.qub.ac.uk organization: School of Electronics, Electrical Engineering and Computer Science, Queen’s University of Belfast, Belfast BT9 5AH, United Kingdom
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Keywords	Networked control system Network-induced delay Fast recursive algorithm Cubic spline Numerical approximation Interpolation ARMA model Numerical analysis Applied mathematics Control system Fast algorithm Recursive algorithm
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SubjectTerms	Approximations and expansions Cubic spline Exact sciences and technology Fast recursive algorithm Mathematical analysis Mathematics Network-induced delay Networked control system Numerical analysis Numerical analysis. Scientific computation Numerical approximation Sciences and techniques of general use
Title	A fast model identification method for networked control system
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