Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Neural Computing and Applications
Erschienen in: Neural Computing and Applications 5/2018

21.12.2016 | Original Article

Agent-based consensus on speed in the network-coupled DC motors

verfasst von: Suhaib Masroor, Chen Peng

Erschienen in: Neural Computing and Applications | Ausgabe 5/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this paper, a new agent-based method is proposed to address the speed synchronization problem in the network-connected motors. In this study, DC motor is used, driven by a buck chopper circuit. In the proposed method, the consensus protocol of the leader-following multi-agent system is modified, in order to make consensus on the speed among multiple motors in the network, so that they can attain synchronous speed. In order to have a stable system, a common Lyapunov function is developed such that consensus is said to be reached if the ith agent is controllable and observable. MATLAB is used for the purpose of simulation, and results obtained authorize the proposed methodology.
Vorheriger Artikel Rock strength estimation: a PSO-based BP approach
Nächster Artikel Estimation of cementation factor in carbonate reservoir by using genetic fuzzy inference system

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Sergaki ES, Stavrakakis GS, Pouliezos AD (2002) Optimal robot speed trajectory by minimization of the actuator motor electromechanical losses. J Intell Robot Syst 33(2):187–207CrossRefMATH
2.
González I, Salazar S, Torres J, Lozano R, Romero H (2013) Real-time attitude stabilization of a mini-uav quad-rotor using motor speed feedback. J Intell Robot Syst 70(1–4):93–106CrossRef
3.
Sanchez A, García Carrillo LR, Rondon E, Lozano R, Garcia O (2011) Hovering flight improvement of a quad-rotor mini UAV using brushless DC motors. J Intell Robot Syst 61(1–4):85–101CrossRef
4.
Nunez C, Alvarez R, Cervantes I (2004) Comparison of multi-motor synchronization techniques. In: Industrial electronics society, 2004. IECON 2004. 30th annual conference of IEEE, vol 2, pp 1670–1675. IEEE
5.
Lee H-H, Jeong U-H (2000) A study on speed synchronization for multi-motors using controller area network. In: Science and technology, 2000. KORUS 2000. Proceedings. The 4th Korea–Russia international symposium on, vol 2, pp 234–239. IEEE
6.
Pérez-Pinal FJ, Nunez C, Alvarez R (2005) Multi-motor synchronization technique applied in traction devices. In: IEEE international conference on electric machines and drives, 2005
7.
Chen S, Zhang K, Zhang W, Shi Z, Liu C, Chen J, Liu T (2010) Design of multi-motor synchronous control system. In: Proceedings of the 29th Chinese control conference, pp 3367–3371. IEEE
8.
Fucai L, Xuelian Z, Liwei L (2002) Synchronous control theory and practical study of multi-motor synchronous driving system. Control Eng China 9:87–90
9.
Ren J, Li C-W, Zhao D-Z (2009) Linearizing control of induction motor based on networked control systems. Int J Autom Comput 6(2):192–197CrossRef
10.
Zhao D, Zhang S, Li C, Stobart R (2013) Scheduling and control co-design of networked induction motor control systems. In: 2013 IEEE international conference on information and automation (ICIA), pp 880–885
11.
Zhao D, Li C, Ren J (2011) Fuzzy speed control and stability analysis of a networked induction motor system with time delays and packet dropouts. Nonlinear Anal Real World Appl 12(1):273–287MathSciNetCrossRefMATH
12.
Matsuo K, Miura T, Taniguchi T (2006) Speed control of a dc motor system through delay time variant network. In: 2006 SICE-ICASE international joint conference, pp 399–404. IEEE
13.
Almutairi NB, Chow M-Y, Tipsuwan Y (2001) Network-based controlled DC motor with fuzzy compensation. In: Industrial electronics society, 2001. IECON’01. The 27th annual conference of the IEEE, vol 3, pp 1844–1849. IEEE
14.
Sheikholeslami M, Sheykholeslami FB, Khoshhal S, Mola-Abasia H, Ganji DD, Rokni HB (2014) Effect of magnetic field on Cu–water nanofluid heat transfer using GMDH-type neural network. Neural Comput Appl 25(1):171–178CrossRef
15.
Sheikholeslami M, Ganji DD (2016) Heat transfer improvement in a double pipe heat exchanger by means of perforated turbulators. Energy Convers Manag 127:112–123CrossRef
16.
Sheikholeslami M, Ganji DD (2016) Heat transfer enhancement in an air to water heat exchanger with discontinuous helical turbulators; experimental and numerical studies. Energy 116:341–352CrossRef
17.
Olfati-Saber R, Fax A, Murray RM (2007) Consensus and cooperation in networked multi-agent systems. Proc IEEE 95(1):215–233CrossRefMATH
18.
Wang C, Ji H (2014) Leader-following consensus of multi-agent systems under directed communication topology via distributed adaptive nonlinear protocol. Syst Control Lett 70:23–29MathSciNetCrossRefMATH
19.
Hu J, Hong Y (2007) Leader-following coordination of multi-agent systems with coupling time delays. Phys A Stat Mech Appl 374(2):853–863CrossRef
20.
Xie T, Liao X, Li H (2016) Leader-following consensus in second-order multi-agent systems with input time delay: an event-triggered sampling approach. Neurocomputing 177:130–135CrossRef
21.
Djaidja S, Wu QH (2015) Stochastic consensus of leader-following multi-agent systems under additive measurement noises and time-delays. Eur J Control 23:55–61MathSciNetCrossRefMATH
22.
Hu A-H, Hu M, Guo L (2014) Consensus of a leader-following multi-agent system with negative weights and noises. IET Control Theory Appl 8(2):114–119MathSciNetCrossRefMATH
23.
Hong Y, Hu J, Gao L (2006) Tracking control for multi-agent consensus with an active leader and variable topology. Automatica 42(7):1177–1182MathSciNetCrossRefMATH
24.
Hu J, Feng G (2010) Distributed tracking control of leader–follower multi-agent systems under noisy measurement. Automatica 46(8):1382–1387MathSciNetCrossRefMATH
25.
Godsil C, Royle GF (2013) Algebraic graph theory, vol 207. Springer Science & Business Media, New YorkMATH
26.
Li Z, Duan Z (2014) ”Cooperative control of multi-agent systems: a consensus region approach” Automation and Control Engineering. CRC Press, Boca RatonCrossRef
27.
Mesbahi M, Egerstedt M (2010) Graph theoretic methods in multiagent networks. Princeton University Press, PrincetonCrossRefMATH
28.
Peng K, Yang Y (2009) Leader-following consensus problem with a varying-velocity leader and time-varying delays. Physica A 388:193–208CrossRef
29.
Horn RA, Johnson CR (2012) Matrix analysis. Cambridge University Press, CambridgeCrossRef
30.
Xu W, Ho DWC, Li L, Cao J (2015) Leader-following consensus of general linear multi-agent systems: event-triggered schemes. In: Control conference (ASCC), 2015 10th Asian, pp 1–6. IEEE
Metadaten
Titel
Agent-based consensus on speed in the network-coupled DC motors
verfasst von
Suhaib Masroor
Chen Peng
Publikationsdatum
21.12.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 5/2018
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2773-y

Weitere Artikel der Ausgabe 5/2018

Neural Computing and Applications 5/2018 Zur Ausgabe

Original Article

Optimization and predictive modeling using S/N, RSM, RA and ANNs for micro-electrical discharge drilling of AISI 304 stainless steel

Original Article

Applications of non-integer Caputo time fractional derivatives to natural convection flow subject to arbitrary velocity and Newtonian heating

Review

Fault detection, location and classification of a transmission line

Original Article

Information system selection for a supply chain based on current trends: the BRIGS approach

Original Article

Recommender system with grey wolf optimizer and FCM

Original Article

A novel hybrid method based on fuzzy cognitive maps and fuzzy clustering algorithms for grading celiac disease