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Research Papers

Fuzzy Speed Control of Networked Motion Control Systems

[+] Author and Article Information
Shangmin Zhang

Department of Automation,
Tsinghua University,
Beijing 100084, China
e-mail: zhang-sm09@mails.tsinghua.edu.cn

Dezong Zhao

Department of Aeronautical and
Automotive Engineering,
Loughborough University,
Loughborough, Leicester LE11 3TU, UK
e-mail: d.zhao2@lboro.ac.uk

Chunwen Li

Department of Automation,
Tsinghua University,
Beijing 100084, China
e-mail: lcw@mail.tsinghua.edu.cn

Richard Stobart

Department of Aeronautical and
Automotive Engineering,
Loughborough University,
Loughborough, Leicester LE11 3TU, UK
e-mail: r.k.stobart@lboro.ac.uk

Contributed by the Design Engineering Division of ASME for publication in the JOURNAL OF COMPUTATIONAL AND NONLINEAR DYNAMICS. Manuscript received May 31, 2014; final manuscript received February 11, 2015; published online April 9, 2015. Assoc. Editor: Hiroshi Yabuno.

J. Comput. Nonlinear Dynam 10(6), 061013 (Nov 01, 2015) (9 pages) Paper No: CND-14-1144; doi: 10.1115/1.4029903 History: Received May 31, 2014; Revised February 11, 2015; Online April 09, 2015

This paper proposed an integrated scheme for the modeling and control of induction motors in the networked environment. The networked control system (NCS) is built in hierarchical structure, which consists of a networked speed controller and a local controller. In the networked speed controller, fuzzy gain scheduling is applied to guarantee the robustness against communication constraints. Furthermore, a state predictor is designed to compensate the time delay occurred in data transmission from the sensor to the controller, as a component of the networked speed controller. Simulation and experimental results are given to illustrate the effectiveness of the proposed approach.

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References

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Figures

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Fig. 1

Structure of the investigated NMCS

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Fig. 2

State flow of the predictor

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Fig. 3

Membership functions of the input e, and outputs KP and KI

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Fig. 4

Timing diagram of the signals in the NMCS

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Fig. 5

Data transmission in the NMCS with packets dropout

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Fig. 6

Control performance evaluation at constant τ. Induction motor output speed at (a) τ = 5 ms and (b) τ = 20 ms.

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Fig. 7

Control performance evaluation at time-varying τ. (a) Induction motor output speed at (a) 1 ms ≤ τ ≤ 5 ms and (b) 5 ms ≤ τ ≤ 20 ms.

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Fig. 8

State predictor performance evaluation at constant τ. Induction motor output speed at (a) τ = 5 ms and (b) τ = 20 ms.

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Fig. 9

State predictor performance evaluation at time-varying τ. Induction motor output speed at (a) 1 ms ≤ τ ≤ 5 ms and (b) 5 ms ≤ τ ≤ 20 ms.

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Fig. 10

Control performance evaluation with packets dropout. Induction motor output speed at (a) r = 30% and (b) r = 60%.

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Fig. 11

Structure of the NMCS experiment platform

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Fig. 12

NMCS experiment platform

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Fig. 13

Experimental results using different networked controllers

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