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
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
International Journal of Machine Learning and Cybernetics
Erschienen in: International Journal of Machine Learning and Cybernetics 5/2016

01.10.2016 | Original Article

Mixed \(H_2/H_{\infty }\) pitch control of wind turbine generator system based on global exact linearization and regional pole placement

verfasst von: Mu Zhu, Jizhen Liu, Zhongwei Lin, Hongmin Meng

Erschienen in: International Journal of Machine Learning and Cybernetics | Ausgabe 5/2016

Einloggen

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

search-config
loading …

Abstract

When the wind power electricity system working above the rated wind speed, the disturbed wind speed can lead to the output ripple easily, which causes a significant negative influence on the stability of the power grid. In order to overcome this disadvantage, this paper discusses the mixed \(H_2/H_{\infty }\) pitch angle control design problem for the nonlinear wind turbine generator system, where the turbulence is regarded as the disturbance input. Especially, the global exact linearization and the pole placement techniques are also applied to guarantee the desired control performance and expected dynamic characteristics in the situation of a large-scale variety of the system operation points. The simulation results show the effectiveness of the proposed method.
Vorheriger Artikel Improved probabilistic neural network PNN and its application to defect recognition in rock bolts

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

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

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"

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
Weitere Produktempfehlungen anzeigen
Literatur
1.
2.
Muyeen SM (2012) Wind energy conversion systems: technology and trends. Springer, BerlinCrossRef
3.
Jha AR (2011) Wind turbine technology. CRC Press, Florida
4.
Mathew S, Philip GS (2011) Advances in wind energy conversion technology. Springer, Berlin
5.
Munteanu L, Bratcu AL, Cutuluis NA (2008) Optimal control of wind energy systems. Springer, London
6.
Senjyu T, Sakamoto R, Urasaki N et al (2006) Output power leveling of wind turbine generator for all operating regions by pitch angle control. IEEE Trans Energy Convers 21:467–475CrossRef
7.
El-Tous Y (2008) Pitch angle control of variable speed wind turbine. Am J Eng Appl Sci 2:118–120CrossRef
8.
Lescher F, Zhao JY, Borne P (2005) Robust gain scheduling controller for pitch regulated variable speed wind turbine. Stud Inform Control 14:299–315
9.
Bianchi FD, Mantz RJ, Christiansen CF (2005) Gain scheduling control of variable speed wind energy conversion systems using quasi-LPV models. Control Eng Pract 13:247–255CrossRef
10.
Balas MJ, Wright A, Hand M et al (2003) Dynamics and control of horizontal axis wind turbines. In: The American control conference, Denver, Colorado, USA, pp 3781–3793
11.
Slotha C, Esbensenb T, Stoustrup J (2011) Robust and fault-tolerant linear parameter-varying control of wind turbines. Mechatronics 21:645–659CrossRef
12.
Bianchi FD, Battista HD, Mantz RJ (2007) Wind turbine control systems principles, modelling and gain scheduling design. Springer, Netherlands
13.
14.
Khalil HK (2002) Nonlinear system. Prentice Hall, London
15.
Cheng D, Isidori A, Respondek W, Tarn TJ (1988) Exact linearization of nonlinear systems with outputs. Math Syst Theory 21:63–83MathSciNetCrossRefMATH
16.
Lin ZW, Lin Y, Zhang WH (2009) A unified design for state and output feedback \(H_{\infty }\) control of nonlinear stochastic Markovian jump systems with state and disturbance-dependent noise. Automatica 41:2955–2962CrossRefMATH
17.
Lin ZW, Liu JZ, Zhang WH, Niu YG (2011) Stabilization of interconnected nonlinear stochastic Markovian jump systems via dissipativity approach. Automatica 47:2796–2800MathSciNetCrossRefMATH
18.
Liu J, Meng H, Hu Y et al (2015) A novel MPPT method for enhancing energy conversion efficiency taking power smoothing into account. Energy Convers Manag 101:738–748CrossRef
19.
Su X, Wu L, Shi P et al (2014) A novel approach to output feedback control of fuzzy stochastic systems. Automatica 50(12):3268–3275MathSciNetCrossRefMATH
20.
Wang J (2014) Adaptive fuzzy control of direct-current motor dead-zone systems. Int J Innov Comput Inform Control 10(4):1391–1399
21.
Su X, Shi P, Wu L et al (2013) A novel control design on discrete-time Takagi–Sugeno fuzzy systems with time-varying delays. IEEE Trans Fuzzy Syst 21(4):655–671CrossRef
22.
Wu L, Su X, Shi P (2015) Fuzzy control of nonlinear electromagnetic suspension systems. In: Fuzzy control systems with time-delay and stochastic perturbation. Springer International Publishing, Berlin, pp 289–307
23.
Li YM, Tong SC, Li TS (2015) Observer-based adaptive fuzzy tracking control of MIMO stochastic nonlinear systems with unknown control direction and unknown dead-zones. IEEE Trans Fuzzy Syst 23(4):1228–1241CrossRef
24.
Li YM, Tong SC, Liu YJ, Li TS (2014) Adaptive fuzzy robust output feedback control of nonlinear systems with unknown dead zones based on small-gain approach. IEEE Trans Fuzzy Syst 22(1):164–176CrossRef
25.
Mistler V, Benallegue A, M’Sirdi NK (2001) Exact linearization and noninteracting control of a 4 rotors helicopter via dynamic feedback. In: IEEE international workshop on robot and human interactive communication, Bordeaux, Paris, pp 586–593
26.
Chang LY, Chen HC (2014) Linearization and input–output decoupling for nonlinear control of proton exchange membrane fuel cells. Energies 7:591–606CrossRef
27.
Famouri P (1992) Control of a linear permanent magnet brushless dc motor via exact linearization methods. IEEE Trans Energy Convers 7:544–551CrossRef
28.
Chilali M, Gahinet P (1996) \(H_{\infty }\) design with pole placement constrains: an LMI approach. IEEE Trans Autom Control 41:358–367MathSciNetCrossRefMATH
29.
30.
Hassan HM, ElShafei AL, Farag WA, Saad MS (2012) A robust LMI-based pitch controller for large wind turbines. Renew Energy 4:63–71CrossRef
31.
Salle SA, Reardon D, Leithead WE, Grimble MJ (1990) Review of wind turbine control. Int J Control 52:1295–1310CrossRef
32.
Abdin ES, Xu W (2000) Control design and dynamic performance analysis of a wind turbine-induction generator unit. IEEE Trans EC 15:91–96
33.
Golnaraghi F, Kuo BC (2010) Automatic control system, 9th edn. Wiley, USA
34.
Dou ZL, Cheng MZ, Ling ZB et al (2010) An adjustable pitch control system in a large wind turbine based on a fuzzy-PID controller. In: International symposium on power electronics electrical drives automation and motion, pp 391–395
Metadaten
Titel
Mixed pitch control of wind turbine generator system based on global exact linearization and regional pole placement
verfasst von
Mu Zhu
Jizhen Liu
Zhongwei Lin
Hongmin Meng
Publikationsdatum
01.10.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Machine Learning and Cybernetics / Ausgabe 5/2016
Print ISSN: 1868-8071
Elektronische ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0519-x

Weitere Artikel der Ausgabe 5/2016

International Journal of Machine Learning and Cybernetics 5/2016 Zur Ausgabe

Original Article

Multi-objective cost-sensitive attribute reduction on data with error ranges

Original Article

Hesitant fuzzy linguistic linear programming technique for multidimensional analysis of preference for multi-attribute group decision making

Original Article

Fuzzy adaptive synchronization of uncertain fractional-order chaotic systems

Original Article

A supervised term selection technique for effective text categorization

Original Article

Novel stability condition of stochastic fuzzy neural networks with Markovian jumping under impulsive perturbations

Original Article

Dual hesitant fuzzy group decision making method and its application to supplier selection

Neuer Inhalt

    Bildnachweise