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A Neural Network Approach for Tracking Control of Uncertain Switched Nonlinear Systems with Unknown Dead-Zone Input

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Abstract

This paper is concerned with adaptive neural tracking control problem for uncertain switched nonlinear systems with unknown dead-zone input. Multilayer neural networks (MNNs) are employed to approximate unknown nonlinear functions, and an adaptive neural network controller is introduced to enhance system robustness. With the proposed control scheme, boundedness of all the signals of the closed-loop system is established regardless of the parameter adjustment mechanism, and better tracking control performance can eventually be achieved in view of the universal approximation capability of MNNs. Also, a switching signal is suitably defined using average dwell-time technique. By using a switching control scheme, it is demonstrated that the transient performance and stability can be simultaneously obtained. Finally, a simulation example is given to illustrate the effectiveness and validity of this approach.

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References

  1. M. Branicky, Multiple Lyapunov functions and other analysis tools for switched and hybrid systems. IEEE Trans. Autom. Control 43(4), 475–482 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  2. M.L. Chiang, L.C. Fu, Adaptive stabilization of a class of uncertain switched nonlinear systems with backstepping control. Automatica 50(8), 2128–2135 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  3. T.T. Han, S.S. Ge, T.T. Lee, Adaptive neural control for a class of switched nonlinear systems. Syst. Control Lett. 58, 109–118 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  4. J. Hespanha, A.S. Morse, Stability of switched systems with average dwell-time. In Proceedings of the 38th IEEE Conference on Decision and Control, Phoenix, Arizona, 1999, pp. 2655–2660

  5. S. Ibrir, W.F. Xie, C.Y. Su, Adaptive tracking of nonlinear systems with non-symmetric dead-zone input. Automatica 43, 522–530 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  6. J. Lin, S. Fei, Q. Wu, Reliable H\(\infty \) filtering for discrete-time switched singular systems with time-varying delay. Circuits Syst. Signal Process. 31(3), 1191–1214 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  7. Y.M. Li, S.C. Tong, Y.J. Liu, T.S. Li, Adaptive fuzzy robust output feedback control of nonlinear systems with unknown dead zones based on small-gain approach. IEEE Trans. Fuzzy Syst. 22(1), 164–176 (2014)

    Article  Google Scholar 

  8. H.Y. Li, J.Y. Yu, C. Hilton, H.H. Liu, Adaptive sliding mode control for nonlinear active suspension vehicle systems using T–S fuzzy approach. IEEE Trans. Ind. Electron. 60(8), 3328–3338 (2013)

    Article  Google Scholar 

  9. D. Liberzon, Switching in Systems and Control (Birkhauser, Boston, 2003)

    Book  MATH  Google Scholar 

  10. Y.J. Liu, N. Zhou, Observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systems with unknown dead-zone input. ISA Trans. 49(4), 462–469 (2010)

    Article  Google Scholar 

  11. Y.J. Liu, S.C. Tong, W. Wang, Adaptive fuzzy output tracking control for a class of uncertain nonlinear systems. Fuzzy Sets Syst. 160(19), 2727–2754 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  12. F. Long, S.M. Fei, Neural networks stabilization and disturbance attenuation for nonlinear switched impulsive systems. Neurocomputing 71, 1741–1747 (2008)

    Article  Google Scholar 

  13. H.Y. Li, X. Jing, H.K. Lam et al., Fuzzy sampled-data control for uncertain vehicle suspension systems. IEEE Trans. Cybern. 44(7), 1111–1126 (2014)

    Article  Google Scholar 

  14. H.Y. Li, X.J. Jing, H.R. Karimi, Output-feedback based H-infinity control for active suspension systems with control delay. IEEE Trans. Ind. Electron. 61(1), 436–446 (2014)

    Article  Google Scholar 

  15. H.Y. Li, P. Huijun Gao, X.D.Z. Shi, Fault-tolerant control of Markovian jump stochastic systems via the augmented sliding mode observer approach. Automatica 50(7), 1825–1834 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  16. F.L. Lewis, A. Yesildirek, K. Liu, Multilayer neural network robot controller with guaranteed tracking performance. IEEE Trans. Neural Netw. 7(2), 388–398 (1996)

    Article  Google Scholar 

  17. C.D. Persis, R.D. Santis, A.S. Morse, Switched nonlinear systems with state-dependent dwell-time. Syst. Control Lett. 50, 291–302 (2003)

    Article  MATH  Google Scholar 

  18. Z.D. Sun, S.S. Ge, Analysis and synthesis of switched linear control systems. Automatica 41, 181–195 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  19. Y. Sun, L. Wang, On stability of a class of switched nonlinear systems. Automatica 49(1), 305–307 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  20. S.C. Tong, X.L. He, H.G. Zhang, A combined backstepping and small-gain approach to robust adaptive fuzzy output feedback control. IEEE Trans. Fuzzy Syst. 17(5), 1059–1069 (2009)

    Article  Google Scholar 

  21. S.C. Tong, C.L. Liu, Y.M. Li, Fuzzy-adaptive decentralized output feedback control for large-scale nonlinear systems with dynamical uncertainties. IEEE Trans. Fuzzy Syst. 18(5), 845–861 (2010)

    Article  Google Scholar 

  22. S.C. Tong, Y. Li, Y.M. Li, Y.J. Liu, Observer-based adaptive fuzzy backstepping control for a class of stochastic nonlinear strict-feedback systems. IEEE Trans. Syst. Man Cybern. Part B 41(6), 1693–1704 (2011)

    Article  MathSciNet  Google Scholar 

  23. S.C. Tong, Y.M. Li, Adaptive fuzzy output feedback tracking backstepping control of strict-feedback nonlinear systems with unknown dead zones. IEEE Trans. Fuzzy Syst. 20(1), 168–180 (2012)

    Article  Google Scholar 

  24. S.C. Tong, B.Y. Huo, Y.M. Li, Observer-based adaptive decentralized fuzzy fault-tolerant control of nonlinear large-scale systems with actuator failures. IEEE Trans. Fuzzy Syst. 22(1), 1–15 (2014)

    Article  Google Scholar 

  25. S.C. Tong, X.L. He, Y.M. Li, Direct adaptive fuzzy backstepping robust control for single input and single output uncertain nonlinear systems using small-gain approach. Inf. Sci. 180, 1738–1758 (2010)

  26. S. Tong, T. Wang, Y. Li, H. Zhang, Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics. IEEE Trans. Cybern. 44(6), 910–921 (2014)

    Article  Google Scholar 

  27. T. Wang, Y. Zhang, J. Qiu, H. Gao, Adaptive fuzzy backstepping control for a class of nonlinear systems with sampled and delayed measurements. IEEE Trans. Fuzzy Syst. (2014). doi:10.1109/TFUZZ.2014.2312026

    Google Scholar 

  28. X.S. Wang, C.Y. Su, H. Hong, Robust adaptive control of a class of nonlinear systems with unknown dead-zone. Automatica 40, 407–413 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  29. Y. Wang, V. Gupta, P.J. Antsaklis, On passivity of a class of discrete-time switched nonlinear systems. IEEE Trans. Autom. Control 59(3), 692–702 (2014)

    Article  MathSciNet  Google Scholar 

  30. G.M. Xie, L. Wang, Controllability and stabilizability of switched linear-systems. Syst. Control Lett. 48(2), 135–155 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  31. H. Yang, V. Cocquempot, B. Jiang, On stabilization of switched nonlinear systems with unstable modes. Syst. Control Lett. 58, 703–708 (2009)

    Article  MathSciNet  Google Scholar 

  32. L. Yu, S.M. Fei, X. Li, Robust adaptive neural tracking control for a class of switched affine nonlinear systems. Neurocomputing 73(10–12), 2274–2279 (2010)

    Article  Google Scholar 

  33. S.J. Yoo, J.B. Park, Y.H. Choi, Decentralized adaptive stabilization of interconnected nonlinear systems with unknown non-symmetric dead-zone inputs. Automatica 45, 436–443 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  34. L. Yu, S.M. Fei, J. Huang, Y. Gao, Trajectory switching control of robotic manipulators based on RBF neural networks. Circuits Syst. Signal Process. 33(4), 1119–1133 (2014)

    Article  MathSciNet  Google Scholar 

  35. C.G. Yang, S.S. Ge, T.H. Lee, Output feedback adaptive control of a class of nonlinear discrete-time systems with unknown control directions. Automatica 45(1), 270–276 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  36. G.S. Zhai, B. Hu, K. Yasuda, A.N. Michel, Disturbance attenuation properties of time-controlled switched systems. J. Franklin Inst. 338(7), 765–779 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  37. T.P. Zhang, S.S. Ge, Adaptive neural control of MIMO nonlinear state time-varying delay systems with unknown dead-zones and gain signs. Automatica 43(6), 1021–1033 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  38. J. Zhao, D.J. Hill, Dissipativity theory for switched systems. IEEE Trans. Autom. Control 53(4), 941–953 (2008)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgments

The work is supported by the National Natural Science Foundation of China (No. 61403268), Natural Science Foundation of Jiangsu Province, China (No. BK20130331), Open Project from digital manufacture technology Key Laboratory of JiangSu Province (No. HGDML-1105), and the Foundation of Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, China (No. MCCSE2013A01). The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.

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Authors and Affiliations

  1. School of Mechanical and Electric Engineering, Soochow University, Suzhou, 215021, China

    Lei Yu

  2. Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, Southeast University, Nanjing, 210096, China

    Shumin Fei

  3. Digital Manufacture Technology Key Laboratory of JiangSu Province, Huaian, 223003, China

    Gang Yang

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  1. Lei Yu
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  2. Shumin Fei
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  3. Gang Yang
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Correspondence to Lei Yu.

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Yu, L., Fei, S. & Yang, G. A Neural Network Approach for Tracking Control of Uncertain Switched Nonlinear Systems with Unknown Dead-Zone Input. Circuits Syst Signal Process 34, 2695–2710 (2015). https://doi.org/10.1007/s00034-015-9971-1

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  • DOI: https://doi.org/10.1007/s00034-015-9971-1

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