Skip to main content
Erschienen in: Neural Computing and Applications 5/2013

01.10.2013 | Original Article

Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation

verfasst von: Yongming Li, Shaocheng Tong, Tieshan Li

Erschienen in: Neural Computing and Applications | Ausgabe 5/2013

Einloggen

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

search-config
loading …

Abstract

In this paper, a novel direct adaptive fuzzy control approach is presented for uncertain nonlinear systems in the presence of input saturation. Fuzzy logic systems are directly used to tackle unknown nonlinear functions, and the adaptive fuzzy tracking controller is constructed by using the backstepping recursive design techniques. To overcome the problem of input saturation, a new auxiliary design system and Nussbaum gain functions are incorporated into the control scheme, respectively. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converges to a small neighborhood of the origin. A simulation example is included to illustrate the effectiveness of the proposed approach. Two key advantages of the scheme are that (i) the direct adaptive fuzzy control method is proposed for uncertain nonlinear system with input saturation by using Nussbaum function technique and (ii) The number of the online adaptive learning parameters is reduced.

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!

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!

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!

Literatur
1.
Zurück zum Zitat Zhang HG, Quan YB (2001) Modeling, identification, and control of a class of nonlinear systems. IEEE Trans Fuzzy Syst 9(2):349–354CrossRef Zhang HG, Quan YB (2001) Modeling, identification, and control of a class of nonlinear systems. IEEE Trans Fuzzy Syst 9(2):349–354CrossRef
2.
Zurück zum Zitat Zhang HG, Cai L, Bien Z (2000) A fuzzy basis function vector-based multivariable adaptive controller for nonlinear systems. IEEE Trans Syst Man Cybern B 30(1):210–217CrossRef Zhang HG, Cai L, Bien Z (2000) A fuzzy basis function vector-based multivariable adaptive controller for nonlinear systems. IEEE Trans Syst Man Cybern B 30(1):210–217CrossRef
3.
Zurück zum Zitat Wang ZS, Zhang HG (2010) Global asymptotic stability of reaction-diffusion cohen-grossberg neural networks with continuously distributed delays. IEEE Trans Neural Networks 21(1):39–49CrossRef Wang ZS, Zhang HG (2010) Global asymptotic stability of reaction-diffusion cohen-grossberg neural networks with continuously distributed delays. IEEE Trans Neural Networks 21(1):39–49CrossRef
4.
Zurück zum Zitat Wang ZS, Zhang HG, Li P (2010) An LMI approach to stability analysis of reaction-diffusion Cohen-Grossberg neural networks concerning with Dirichlet boundary conditions and distributed delays. IEEE Trans Syst Man Cybern B 40(6):1596–1606CrossRef Wang ZS, Zhang HG, Li P (2010) An LMI approach to stability analysis of reaction-diffusion Cohen-Grossberg neural networks concerning with Dirichlet boundary conditions and distributed delays. IEEE Trans Syst Man Cybern B 40(6):1596–1606CrossRef
5.
Zurück zum Zitat Wang LX (1994) Adaptive fuzzy systems and control: design and stability analysis. Prentice- Hall, Englewood Cliffs, NJ Wang LX (1994) Adaptive fuzzy systems and control: design and stability analysis. Prentice- Hall, Englewood Cliffs, NJ
6.
Zurück zum Zitat Chen BS, Lee CH, Chang YC (1996) H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach. IEEE Trans Fuzzy Syst 4(2):32–43CrossRef Chen BS, Lee CH, Chang YC (1996) H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach. IEEE Trans Fuzzy Syst 4(2):32–43CrossRef
7.
Zurück zum Zitat Spooner JT, Passino KM (1996) Stable adaptive control of a class of nonlinear systems and neural network. IEEE Trans Fuzzy Syst 4(4):339–359CrossRef Spooner JT, Passino KM (1996) Stable adaptive control of a class of nonlinear systems and neural network. IEEE Trans Fuzzy Syst 4(4):339–359CrossRef
8.
Zurück zum Zitat Li HX, Tong SC (2003) A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems. IEEE Trans Fuzzy Syst 11(1):24–34CrossRef Li HX, Tong SC (2003) A hybrid adaptive fuzzy control for a class of nonlinear MIMO systems. IEEE Trans Fuzzy Syst 11(1):24–34CrossRef
9.
Zurück zum Zitat Tong SC, Li HX, Chen GR (2004) Adaptive fuzzy control for decentralized control for a class of large-scale nonlinear systems. IEEE Trans Syst Man Cybern B 34(1):770–775CrossRef Tong SC, Li HX, Chen GR (2004) Adaptive fuzzy control for decentralized control for a class of large-scale nonlinear systems. IEEE Trans Syst Man Cybern B 34(1):770–775CrossRef
10.
Zurück zum Zitat Wu HN, Cai KY (2007) Robust fuzzy control for uncertain discrete-time nonlinear Markovian jump systems without mode observations. Inf Sci 177(6):1509–1522MathSciNetCrossRefMATH Wu HN, Cai KY (2007) Robust fuzzy control for uncertain discrete-time nonlinear Markovian jump systems without mode observations. Inf Sci 177(6):1509–1522MathSciNetCrossRefMATH
11.
Zurück zum Zitat Liu YJ, Zheng YQ (2009) Adaptive robust fuzzy control for a class of uncertain chaotic systems. Nonlinear Dyn 57(3):431–439MathSciNetCrossRefMATH Liu YJ, Zheng YQ (2009) Adaptive robust fuzzy control for a class of uncertain chaotic systems. Nonlinear Dyn 57(3):431–439MathSciNetCrossRefMATH
12.
Zurück zum Zitat Kristic M, Kanellakopoulos I, Kokotovic PV (1995) Nonlinear and adaptive control design. Wiley, New York Kristic M, Kanellakopoulos I, Kokotovic PV (1995) Nonlinear and adaptive control design. Wiley, New York
13.
Zurück zum Zitat Chen B, Liu XP (2005) Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping and application to chemical processes. IEEE Trans Fuzzy Syst 13(6):832–847CrossRef Chen B, Liu XP (2005) Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping and application to chemical processes. IEEE Trans Fuzzy Syst 13(6):832–847CrossRef
14.
Zurück zum Zitat Liu YJ, Wang W, Tong SC, Liu YS (2010) Robust adaptive tracking control for nonlinear systems based on bounds of fuzzy approximation parameters. IEEE Trans Syst Man Cybern A 40(1):170–184CrossRef Liu YJ, Wang W, Tong SC, Liu YS (2010) Robust adaptive tracking control for nonlinear systems based on bounds of fuzzy approximation parameters. IEEE Trans Syst Man Cybern A 40(1):170–184CrossRef
15.
Zurück zum Zitat Khaled RB, Mnasri C, Gasmi M (2011) Direct adaptive fuzzy control of nonlinear systems in pure feedback form. 9th IEEE Int Conf Control Autom 1:324–329 Khaled RB, Mnasri C, Gasmi M (2011) Direct adaptive fuzzy control of nonlinear systems in pure feedback form. 9th IEEE Int Conf Control Autom 1:324–329
16.
Zurück zum Zitat Yang YS, Feng G, Ren JS (2004) A combined backstepping and small-gain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems. IEEE Trans Syst Man Cybern A 34(3):406–420CrossRef Yang YS, Feng G, Ren JS (2004) A combined backstepping and small-gain approach to robust adaptive fuzzy control for strict-feedback nonlinear systems. IEEE Trans Syst Man Cybern A 34(3):406–420CrossRef
17.
Zurück zum Zitat Yang YS, Zhou CJ (2005) Adaptive fuzzy H∞ stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach. IEEE Trans Fuzzy Syst 13(1):104–114CrossRef Yang YS, Zhou CJ (2005) Adaptive fuzzy H∞ stabilization for strict-feedback canonical nonlinear systems via backstepping and small-gain approach. IEEE Trans Fuzzy Syst 13(1):104–114CrossRef
18.
Zurück zum Zitat Ge SS, Wang C (2002) Direct adaptive NN control of a class of nonlinear systems. IEEE Trans Neural Networks 13(1):214–221MathSciNetCrossRef Ge SS, Wang C (2002) Direct adaptive NN control of a class of nonlinear systems. IEEE Trans Neural Networks 13(1):214–221MathSciNetCrossRef
19.
Zurück zum Zitat Chen WS, Jiao LC, Li RH, Li J (2010) Adaptive backstepping fuzzy control for nonlinearly parameterized systems with periodic disturbances. IEEE Trans Fuzzy Syst 18(4):674–685CrossRef Chen WS, Jiao LC, Li RH, Li J (2010) Adaptive backstepping fuzzy control for nonlinearly parameterized systems with periodic disturbances. IEEE Trans Fuzzy Syst 18(4):674–685CrossRef
20.
Zurück zum Zitat Chen WS, Jiao LC (2010) Adaptive tracking for periodically time-varying and nonlinearly parameterized systems using multilayer neural networks. IEEE Trans Neural Networks 21(2):345–351CrossRef Chen WS, Jiao LC (2010) Adaptive tracking for periodically time-varying and nonlinearly parameterized systems using multilayer neural networks. IEEE Trans Neural Networks 21(2):345–351CrossRef
21.
Zurück zum Zitat Zhang TP, Wen H, Zhu Q (2010) Adaptive fuzzy control of nonlinear systems in pure-feedback form based on input-to state stability. IEEE Trans Fuzzy Syst 18(2):1–13CrossRef Zhang TP, Wen H, Zhu Q (2010) Adaptive fuzzy control of nonlinear systems in pure-feedback form based on input-to state stability. IEEE Trans Fuzzy Syst 18(2):1–13CrossRef
22.
Zurück zum Zitat Liu YJ, Wang W (2007) Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems. Inf Sci 177(18):3901–3917CrossRefMATH Liu YJ, Wang W (2007) Adaptive fuzzy control for a class of uncertain nonaffine nonlinear systems. Inf Sci 177(18):3901–3917CrossRefMATH
23.
Zurück zum Zitat Tong SC, He XL, Zhang HG (2009) A combined backstepping and small-gain approach to robust adaptive fuzzy output feedback control. IEEE Trans Fuzzy Syst 17(5):1059–1069CrossRef Tong SC, He XL, Zhang HG (2009) A combined backstepping and small-gain approach to robust adaptive fuzzy output feedback control. IEEE Trans Fuzzy Syst 17(5):1059–1069CrossRef
24.
Zurück zum Zitat Tong SC, Li YM (2009) Observer-based fuzzy adaptive control for strict-feedback nonlinear systems. Fuzzy Sets Syst 160(12):1749–1764MathSciNetCrossRefMATH Tong SC, Li YM (2009) Observer-based fuzzy adaptive control for strict-feedback nonlinear systems. Fuzzy Sets Syst 160(12):1749–1764MathSciNetCrossRefMATH
25.
Zurück zum Zitat Wang T, Tong SC, Li YM (2009) Robust adaptive fuzzy control for nonlinear system with dynamic uncertainties based on backstepping. Int J Innov Comput Inf Control 5(9):2675–2688 Wang T, Tong SC, Li YM (2009) Robust adaptive fuzzy control for nonlinear system with dynamic uncertainties based on backstepping. Int J Innov Comput Inf Control 5(9):2675–2688
26.
Zurück zum Zitat Chen WS, Li JM (2008) Decentralized output-feedback neural control for systems with unknown interconnections. IEEE Trans Syst Man Cybern 38(1):258–266CrossRef Chen WS, Li JM (2008) Decentralized output-feedback neural control for systems with unknown interconnections. IEEE Trans Syst Man Cybern 38(1):258–266CrossRef
27.
Zurück zum Zitat Tong SC, Liu CL, Li YM (2010) Fuzzy adaptive decentralized control for large-scale nonlinear systems with dynamical uncertainties. IEEE Trans Fuzzy Syst 18(5):845–861CrossRef Tong SC, Liu CL, Li YM (2010) Fuzzy adaptive decentralized control for large-scale nonlinear systems with dynamical uncertainties. IEEE Trans Fuzzy Syst 18(5):845–861CrossRef
28.
Zurück zum Zitat Zhou Q, Shi P, Lu J, Xu S (2011) Adaptive output feedback fuzzy tracking control for a class of nonlinear systems. IEEE Trans Fuzzy Syst 19(5):972–982CrossRef Zhou Q, Shi P, Lu J, Xu S (2011) Adaptive output feedback fuzzy tracking control for a class of nonlinear systems. IEEE Trans Fuzzy Syst 19(5):972–982CrossRef
29.
Zurück zum Zitat Chen WS, Jiao LC, Du ZB (2010) Output-feedback adaptive dynamic surface control of stochastic nonlinear systems using neural network. IET Control Theory Appl 4(12):3012–3021MathSciNetCrossRef Chen WS, Jiao LC, Du ZB (2010) Output-feedback adaptive dynamic surface control of stochastic nonlinear systems using neural network. IET Control Theory Appl 4(12):3012–3021MathSciNetCrossRef
30.
Zurück zum Zitat Chen WS, Jiao LC, Li J, Li RH (2010) Adaptive NN backstepping output-feedback control for stochastic nonlinear strict-feedback systems with time-varying delays. IEEE Trans Syst Man Cybern B 40(3):939–950CrossRef Chen WS, Jiao LC, Li J, Li RH (2010) Adaptive NN backstepping output-feedback control for stochastic nonlinear strict-feedback systems with time-varying delays. IEEE Trans Syst Man Cybern B 40(3):939–950CrossRef
31.
Zurück zum Zitat Zhou J, Meng JE, Zurada JM (2007) Adaptive neural network control of uncertain nonlinear systems with nonsmooth actuator nonlinearities. Neurocomputing 70(4–6):1062–1070CrossRef Zhou J, Meng JE, Zurada JM (2007) Adaptive neural network control of uncertain nonlinear systems with nonsmooth actuator nonlinearities. Neurocomputing 70(4–6):1062–1070CrossRef
32.
Zurück zum Zitat Zhou J (2008) Decentralized adaptive control for large-scale time-delay systems with dead-zone input. Automatica 44(7):1790–1799MathSciNetCrossRefMATH Zhou J (2008) Decentralized adaptive control for large-scale time-delay systems with dead-zone input. Automatica 44(7):1790–1799MathSciNetCrossRefMATH
33.
Zurück zum Zitat Ting CS (2008) A robust fuzzy control approach to stabilization of nonlinear time- delay systems with saturating inputs. Int J Fuzzy Syst 10(1):50–60MathSciNet Ting CS (2008) A robust fuzzy control approach to stabilization of nonlinear time- delay systems with saturating inputs. Int J Fuzzy Syst 10(1):50–60MathSciNet
34.
Zurück zum Zitat Wen CY, Zhou J, Liu ZT, Su HY (2011) Robust adaptive control of uncertain nonlinear systems in the presence of input saturation and external disturbance. IEEE Trans Autom Control 66(7):1672–1678MathSciNetCrossRef Wen CY, Zhou J, Liu ZT, Su HY (2011) Robust adaptive control of uncertain nonlinear systems in the presence of input saturation and external disturbance. IEEE Trans Autom Control 66(7):1672–1678MathSciNetCrossRef
35.
Zurück zum Zitat Li TS, Li RH, Li JF (2011) Decentralized adaptive neural control of nonlinear interconnected large-scale systems with unknown time delays and input saturation. Neurocomputing 74:2277–2283CrossRef Li TS, Li RH, Li JF (2011) Decentralized adaptive neural control of nonlinear interconnected large-scale systems with unknown time delays and input saturation. Neurocomputing 74:2277–2283CrossRef
36.
Zurück zum Zitat Chen M, Ge SS, How BV (2010) Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities. IEEE Trans Neural Networks 21(5):796–812CrossRef Chen M, Ge SS, How BV (2010) Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities. IEEE Trans Neural Networks 21(5):796–812CrossRef
Metadaten
Titel
Direct adaptive fuzzy backstepping control of uncertain nonlinear systems in the presence of input saturation
verfasst von
Yongming Li
Shaocheng Tong
Tieshan Li
Publikationsdatum
01.10.2013
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 5/2013
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-012-0993-3

Weitere Artikel der Ausgabe 5/2013

Neural Computing and Applications 5/2013 Zur Ausgabe