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
Soft Computing
Erschienen in: Soft Computing 2/2021

27.07.2020 | Methodologies and Application

General type-2 fuzzy sliding mode control for motion balance adjusting of power-line inspection robot

verfasst von: Jiahao Liu, Tao Zhao, Songyi Dian

Erschienen in: Soft Computing | Ausgabe 2/2021

Einloggen

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

search-config
loading …

Abstract

In this paper, a novel general type-2 fuzzy sliding mode controller for motion balance adjusting of a power-line inspection robot is developed. The combination method between general type-2 fuzzy system and sliding mode control is different from the existing works. In this paper, sliding mode control is used to finish the motion balance adjusting work. The sliding mode surface is designed according to the Ackermann’s formula. And the general type-2 fuzzy system is used to strengthen the anti-interference ability of the power-line inspection robot. The general type-2 fuzzy sliding mode controller is developed by substituting an element of the sliding mode control law by the output of general type-2 fuzzy system. The novel combination method makes it possible to enhance the anti-interference ability of PLI robot while achieving motion balance control. According to the simulation results, the effectiveness of the proposed controller is proved. And it can also be known that the proposed method is not limited to the GT2FS, and its IT2FS and T1FS counterpart can also strengthen the anti-interference ability in different level.
Vorheriger Artikel Generalized trapezoidal hesitant fuzzy numbers and their applications to multi criteria decision-making problems
Nächster Artikel Partial label learning based on label distributions and error-correcting output codes

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 "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
Literatur
Abdelaal ME, Emara HM, Bahgat A (2013) Interval type 2 fuzzy sliding mode control with application to inverted pendulum on a cart. In: 2013 IEEE international conference on industrial technology (ICIT). IEEE, pp 100–105
Ackermann J, Utkin V (1998) Sliding mode control design based on Ackermann’s formula. IEEE Trans Autom Control 43(2):234–237MathSciNetMATHCrossRef
Bartolini G (1999) A robust control design for a class of uncertain non-linear systems featuring a second-order sliding mode. Int J Control 72(4):321–331MathSciNetMATHCrossRef
Bartolini G, Punta E, Zolezzi T (2004) Simplex methods for nonlinear uncertain sliding-mode control. IEEE Trans Autom Control 49(6):922–933MathSciNetMATHCrossRef
Cai A, Quek C, Maskell DL (2007) Type-2 GA-TSK fuzzy neural network. IEEE Congr Evolut Comput 2007:1578–1585
Cai L, Liang Z, Hou Z, et al (2008) Fuzzy control of the inspection robot for obstacle-negotiation. In: 2008 IEEE international conference on networking, sensing and control. IEEE, pp 117–122
Castillo O (2012) Introduction to type-2 fuzzy logic control. Type-2 fuzzy logic in intelligent control applications. Springer, Berlin, pp 3–5CrossRef
Dian S, Hoang S, Pu M et al (2016) Gain scheduling based backstepping control for motion balance adjusting of a power-line inspection robot. In: 35th Chinese control conference (CCC). IEEE 2016, pp 441–446
Dian S, Chen L, Hoang S et al (2018) Gain scheduled dynamic surface control for a class of underactuated mechanical systems using neural network disturbance observer. Neurocomputing 275:1998–2008CrossRef
Edwards C, Spurgeon S (1998) Sliding mode control: theory and applications. CRC Press, Boca RatonMATHCrossRef
Fei J, Chu Y (2020) Double hidden layer recurrent neural adaptive global sliding mode control of active power filter. IEEE Trans Power Electron 35(3):3069–3084CrossRef
Ghaemi M, Akbarzadeh-Totonchi MR (2014) Indirect adaptive interval type-2 fuzzy PI sliding mode control for a class of uncertain nonlinear systems. Iran J Fuzzy Syst 11(5):1–21MathSciNetMATH
Hirschorn RM (2006) Generalized sliding-mode control for multi-input nonlinear systems. IEEE Trans Autom Control 51(9):1410–1422MathSciNetMATHCrossRef
Hongwen W, Jinna X, Yaoting L et al (2011) Switch gain fuzzy modulation of sliding mode control based on ackermann’s formula. Comput Meas Control 19(12):2979–2981
Hosseini SA, Akbarzadeh TMR, Naghibi-Sistani MB (2013) A synchronizing controller using a direct adaptive interval type-2 fuzzy sliding mode strategy. In: 2013 IEEE international conference on fuzzy systems (FUZZ-IEEE). IEEE, pp 1–8
Hung JY, Gao W, Hung JC (1993) Variable structure control: a survey. IEEE Trans Ind Electron 40(1):2–22CrossRef
Hwang JH, Kang YC, Park JW et al (2017) Advanced interval type-2 fuzzy sliding mode control for robot manipulator. Comput Intell Neurosci 960849:1–11CrossRef
Iglesias E, García Y, Sanjuan M et al (2007) Fuzzy surface-based sliding mode control. ISA Trans 46(1):73–83CrossRef
Juang CF, Hsu CH (2009) Reinforcement ant optimized fuzzy controller for mobile-robot wall-following control. IEEE Trans Ind Electron 56(10):3931–3940CrossRef
Karnik NN, Mendel JM (1998) Type-2 fuzzy logic systems: type-reduction. In: SMC’98 conference proceedings. 1998 IEEE international conference on systems, man, and cybernetics (Cat. No. 98CH36218), vol 2. IEEE, pp 2046–2051
Karnik NN, Mendel JM, Liang Q (1999) Type-2 fuzzy logic systems. IEEE Trans Fuzzy Syst 7(6):643–658CrossRef
Khooban MH, Niknam T (2015) A new and robust control strategy for a class of nonlinear power systems: adaptive general type-II fuzzy. Proc Inst Mech Eng Part I J Syst Control Eng 229(6):517–528
Khooban MH, Alfi A, Abadi DNM (2013) Teaching-learning-based optimal interval type-2 fuzzy PID controller design: a nonholonomic wheeled mobile robots. Robotica 31(7):1059–1071CrossRef
Khooban MH, Niknam T, Blaabjerg F et al (2016a) Free chattering hybrid sliding mode control for a class of non-linear systems: electric vehicles as a case study. IET Sci Meas Technol 10(7):776–785CrossRef
Khooban MH, Niknam T, Sha-Sadeghi M (2016b) A time-varying general type-II fuzzy sliding mode controller for a class of nonlinear power systems. J Intell Fuzzy Syst 30(5):2927–2937MATHCrossRef
Khooban MH, Vafamand N, Liaghat A et al (2017) An optimal general type-2 fuzzy controller for Urban Traffic Network. ISA Trans 66:335–343CrossRef
Li H, Gao Y, Shi P et al (2016a) Observer-based fault detection for nonlinear systems with sensor fault and limited communication capacity. IEEE Trans Autom Control 61(9):2745–2751MathSciNetMATHCrossRef
Li C, Gao J, Yi J et al (2016b) Analysis and design of functionally weighted single-input-rule-modules connected fuzzy inference systems. IEEE Trans Fuzzy Syst 26(1):56–71CrossRef
Li Y, Liu L, Feng G (2018) Robust adaptive output feedback control to a class of non-triangular stochastic nonlinear systems. Automatica 89:325–332MathSciNetMATHCrossRef
Lin TC, Chen MC (2011) Adaptive hybrid type-2 intelligent sliding mode control for uncertain nonlinear multivariable dynamical systems. Fuzzy Sets Syst 171(1):44–71MathSciNetMATHCrossRef
Lin TC, Liu HL, Kuo MJ (2009) Direct adaptive interval type-2 fuzzy control of multivariable nonlinear systems. Eng Appl Artif Intell 22(3):420–430CrossRef
Lin TC, Chen MC, Roopaei M (2011) Synchronization of uncertain chaotic systems based on adaptive type-2 fuzzy sliding mode control. Eng Appl Artif Intell 24(1):39–49CrossRef
Liu F (2008) An efficient centroid type-reduction strategy for general type-2 fuzzy logic system. Inf Sci 178(9):2224–2236MathSciNetCrossRef
Liu J, Wang X (2012) Advanced sliding mode control for mechanical systems. Springer, BerlinMATH
Mendel JM (2014) General type-2 fuzzy logic systems made simple: a tutorial. IEEE Trans Fuzzy Syst 22(5):1162–1182CrossRef
Moha’med O, Al-Jumaily AA (2007) Training type-2 fuzzy system by particle swarm optimization. IEEE Congr Evolut Comput 2007:3442–3446
Nafia N, El Kari A, Ayad H et al (2018) A robust type-2 fuzzy sliding mode controller for disturbed MIMO nonlinear systems with unknown dynamics. Autom J Control Meas Electron Comput Commun 59(2):194–207
Nguyen SD, Vo HD, Seo TI (2017) Nonlinear adaptive control based on fuzzy sliding mode technique and fuzzy-based compensator. ISA Trans 70:309–321CrossRef
Niknam T, Khooban MH, Kavousifard A et al (2014) An optimal type II fuzzy sliding mode control design for a class of nonlinear systems. Nonlinear Dyn 75(1–2):73–83MathSciNetCrossRef
Niu Y, Ho DWC (2006) Design of sliding mode control for nonlinear stochastic systems subject to actuator nonlinearity. IEE Proc Control Theory Appl 153(6):737–744MathSciNetCrossRef
Shahsadeghi M, Khooban MH, Niknam T (2014) A robust and simple optimal type II fuzzy sliding mode control strategy for a class of nonlinear chaotic systems. J Intell Fuzzy Syst 27(4):1849–1859MathSciNetMATHCrossRef
Song Z, Sun K (2014) Adaptive backstepping sliding mode control with fuzzy monitoring strategy for a kind of mechanical system. ISA Trans 53(1):125–133MathSciNetCrossRef
Xie X, Yue D, Peng C (2018) Relaxed real-time scheduling stabilization of discrete-time Takagi–Sugeno fuzzy systems via an alterable-weights-based ranking switching mechanism. IEEE Trans Fuzzy Syst 26(6):3808–3819CrossRef
Xin X, Kaneda M (2007) Swing-up control for a 3-DOF gymnastic robot with passive first joint: design and analysis. IEEE Trans Robot 23(6):1277–1285CrossRef
Xu Y (2010) Multi-timescale nonlinear robust control for a miniature helicopter. IEEE Trans Aerosp Electron syst 46(2):656–671CrossRef
Yang D, Feng Z, Sha R et al (2019) Robust control of a class of under-actuated mechanical systems with model uncertainty. Int J Control 92(7):1567–1579 MathSciNetMATHCrossRef
Yu S, Yu X, Shirinzadeh B et al (2005) Continuous finite-time control for robotic manipulators with terminal sliding mode. Automatica 41(4):1957–1964MathSciNetMATHCrossRef
Zhao T, Dian S (2018) State feedback control for interval type-2 fuzzy systems with time-varying delay and unreliable Communication Links. IEEE Trans Fuzzy Syst 26(2):951–966CrossRef
Zhao T, Liu J, Dian S (2019a) Finite-time control for interval type-2 fuzzy time-delay systems with norm-bounded uncertainties and limited communication capacity. Inf Sci 483:153–173MathSciNetMATHCrossRef
Zhao T, Huang MB, Dian SY (2019c) Stability and stabilization of TS fuzzy systems with two additive time-varying delays. Inf Sci 494:174–192MATHCrossRef
Zhao T, Chen CS, Dian SY (2020a) Local stability and stabilization of uncertain nonlinear systems with two additive time-varying delays. Commun Nonlinear Sci Numer Simul 83:105097MathSciNetMATHCrossRef
Metadaten
Titel
General type-2 fuzzy sliding mode control for motion balance adjusting of power-line inspection robot
verfasst von
Jiahao Liu
Tao Zhao
Songyi Dian
Publikationsdatum
27.07.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 2/2021
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-020-05202-1

Weitere Artikel der Ausgabe 2/2021

Soft Computing 2/2021 Zur Ausgabe

Methodologies and Application

Topic modeling combined with classification technique for extractive multi-document text summarization

Methodologies and Application

Emotion cause detection with enhanced-representation attention convolutional-context network

Methodologies and Application

A hybrid fuzzy-stochastic multi-criteria ABC inventory classification using possibilistic chance-constrained programming

Foundations

Preference-inspired coevolutionary algorithm based on differentiated space for many-objective problems

Methodologies and Application

Design of new fractional order PI–fractional order PD cascade controller through dragonfly search algorithm for advanced load frequency control of power systems

Foundations

A duality for two-sorted lattices

Premium Partner

    Bildnachweise