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Adaptive RCMAC sliding mode control for uncertain nonlinear systems

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Abstract

An adaptive recurrent cerebellar-model-articulation-controller (RCMAC) sliding-mode control (SMC) system is developed for the uncertain nonlinear systems. This adaptive RCMAC sliding-model control (ARCSMC) system is composed of two systems. One is an adaptive RCMAC system utilized as the main controller, in which an RCMAC is designed to identify the system models. Another is a robust controller utilized to achieve system’s robust characteristics, in which an uncertainty bound estimator is developed to estimate the uncertainty bound so that the chattering phenomenon of control effort can be eliminated. The on-line adaptive laws of the ARCSMC system are derived in the sense of Lyapunov so that the system stability can be guaranteed. Finally, a comparison between SMC and ARCSMC for a chaotic system and a car-following system are presented to illustrate the effectiveness of the proposed ARCSMC system. Simulation results demonstrate that the proposed control scheme can achieve favorable control performances for the chaotic system and car-following systems without the knowledge of system dynamic functions.

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References

  1. Slotine J-JE, Li WP (1991) Applied nonlinear control. Prentice-Hall, Englewood Cliffs, NJ

    MATH  Google Scholar 

  2. Hung JY, Gao W, Hung JC (1993) Variable structure control: a survey. IEEE Trans Ind Electron 40(1):2–22

    Article  Google Scholar 

  3. Narendra KS, Parthasarathy K (1990) Identification and control of dynamical systems using neural networks. IEEE Trans Neural Netw 1(1):4–27

    Article  Google Scholar 

  4. Lin CM, Hsu CF (2002) Neural-network-based adaptive control for induction servomotor drive system. IEEE Trans Ind Electron 49(1):115–123

    Article  Google Scholar 

  5. Lin CM, Hsu CF (2003) Neural network hybrid control for antilock braking systems. IEEE Trans Neural Netw 14(2):351–359

    Article  Google Scholar 

  6. Ku CC, Lee KY (1995) Diagonal recurrent neural networks for dynamic systems control. IEEE Trans Neural Netw 6(1):144–156

    Article  Google Scholar 

  7. Lin CM, Hsu CF (2004) Supervisory recurrent fuzzy neural network control of wing rock for slender delta wing. IEEE Trans Fuzzy Syst 12(5):733–742

    Article  Google Scholar 

  8. Wai RJ, Lin FJ (1999) Fuzzy neural network sliding-model position controller for induction servo motor driver. IEEE Proc Electr Power Appl 146(3):297–308

    Article  Google Scholar 

  9. Tsai CH, Chung HY, Yu FM (2004) Neuro-sliding mode control with its applications to seesaw systems. IEEE Trans Neural Netw 15(1):124–134

    Article  Google Scholar 

  10. Da F (2000) Decentralized sliding mode adaptive controller design based on fuzzy neural networks for interconnected uncertain nonlinear systems. IEEE Trans Neural Netw 11(6):1471–1480

    Article  MathSciNet  Google Scholar 

  11. Lane SH, Handelman DA, Gelfand JJ (1992) Theory and development of higher-order CMAC neural networks. IEEE Control Syst Mag 12(2):23–30

    Article  Google Scholar 

  12. Wai RJ, Lin CM, Peng YF (2003) Robust CMAC neural network control for LLCC resonant driving linear piezoelectric ceramic motor. IEE Proc Control Theory Appl 150(3):221–232

    Article  Google Scholar 

  13. Peng YF, Wai RJ, Lin CM (2004) Implementation of LLCC-resonant driving circuit and adaptive CMAC neural network control for linear piezoelectric ceramic motor. IEEE Trans Ind Electron 51(1):35–48

    Article  Google Scholar 

  14. Chiang CT, Lin CS (1996) CMAC with general basis functions. Neural Netw 9(7):1199–1211

    Article  Google Scholar 

  15. Lin CM, Peng YF (2004) Adaptive CMAC-based supervisory control for uncertain nonlinear systems. IEEE Trans Syst Man Cybern B 34(2):1248–1260

    Article  Google Scholar 

  16. Lin CM, Peng YF (2005) Missile guidance law design using adaptive cerebellar model articulation controller. IEEE Trans Neural Netw 16(3):636–644

    Article  Google Scholar 

  17. Wang LX (1994) Adaptive fuzzy systems and control: design and stability analysis. Prentice-Hall, Englewood Cliffs, NJ

    Google Scholar 

  18. Wang CH, Lin TC, Lee TT, Liu HL (2002) Adaptive hybrid intelligent control for uncertain nonlinear dynamical systems. IEEE Trans Syst Man Cybern B 32(5):583–597

    Article  Google Scholar 

  19. Spooner JT, Passino KM (1996)Stable adaptive control using fuzzy systems and neural networks. IEEE Trans Fuzzy Syst 4(3):339–359

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge the partial financial support of the National Science Council of Republic of China through grant NSC 92-2213-E-155-001.

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Authors and Affiliations

  1. Department of Electrical Engineering, Yuan-Ze University, No. 135, Yuandong Rd., 32003, Jhongli City, Taoyuan County, Taiwan, R.O.C.

    Chih-Min Lin & Chiu-Hsiung Chen

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  1. Chih-Min Lin
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  2. Chiu-Hsiung Chen
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Correspondence to Chih-Min Lin.

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Lin, CM., Chen, CH. Adaptive RCMAC sliding mode control for uncertain nonlinear systems. Neural Comput & Applic 15, 253–267 (2006). https://doi.org/10.1007/s00521-006-0027-0

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  • DOI: https://doi.org/10.1007/s00521-006-0027-0

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