Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Economy/regularity fuzzy-logic control of DC railway systems using event-driven approach

Economy/regularity fuzzy-logic control of DC railway systems using event-driven approach

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Add to cart
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)
Add to cart

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IEE Proceedings - Electric Power Applications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

© IEE
Published

A methodology for predictive fuzzy control in an event-driven environment for multiobjective decision making on DC railway systems is presented. Railway operation is assessed by a set of performance indices, and the aim of fuzzy control is to score the best performance among these indices. In particular, the paper addresses regenerative braking in DC railways. The proposed methodology is implemented in two control loops: on each traction station and on each train dwell time at passenger stations.

Inspec keywords: traction; rail traffic; regenerative braking; fuzzy control; traffic control; railways; predictive control

Other keywords: regenerative braking; performance indices; event-driven approach; predictive fuzzy control; train dwell time; fuzzy-logic control; multiobjective decision making; passenger stations; DC railway systems; control loops; traction station

Subjects: Optimal control; Transportation; Rail-traffic system control; Fuzzy control

References

    1. 1)
      • Chew, T.C., Koyama, S.: `4Q/ GTO chopper propulsion control systemfor Singapore MRT', Proceedings of international conference on Mass rapidtransit worldwide, 1986, p. 425–432.
    2. 2)
      • Gondo, T., Hoshino, M., Sawada, K.: `Electrical power system computersimulation', Proceedings of international conference on Mass rapid transitworldwide, 1986, p. 377–396.
    3. 3)
      • Chang, C.S., Thia, B.S.: `Object oriented representation of signalling and train control system in railway operation', 4 th international conference on Computer-aided design, manufactureand operation inrailway and other advance Mass transit systems, September 1994, Madrid, Spain.
    4. 4)
      • C.S. Chang , T.T. Chan , K.K. Lee . AI applications and solutiontechniques for AC railway system control and simulation. IEE Proc. B , 1 , 1 - 12
    5. 5)
      • C.C. Lee . Fuzzy logic in control systems: fuzzy logic controller - Pts 1 &2. IEEE Trans. , 2 , 404 - 435
    6. 6)
      • B. Mellitt , Z.S. Mouneimne , C.J. Goodman . Simulation study of DCtransit systems with inverting substations. IEE Proc. B , 2 , 38 - 50
    7. 7)
      • C.S. Chang . AC train emergency fuzzy logic control using event-drivenapproach. IEE Proc. B , 5 , 307 - 315
    8. 8)
      • J. Arrillaga , C.P. Harnold , B.J. Harker . (1990) Computer analysis of power systems.
http://iet.metastore.ingenta.com/content/journals/10.1049/ip-epa_19960204
Loading

Related content

content/journals/10.1049/ip-epa_19960204
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address