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An adaptive fuzzy sliding mode controller for MEMS triaxial gyroscope with angular velocity estimation

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Abstract

In this paper, an adaptive fuzzy sliding mode control (AFSMC) for Micro-Electro-Mechanical Systems (MEMS) triaxial gyroscope is proposed. First, a novel adaptive identification approach with sliding mode controller which can identify angular velocity and other system parameters is developed. And in order to reduce the chattering, an AFSMC is designed to approximate the upper bound of the uncertainties and external disturbances. Based on Lyapunov methods, these adaptive laws can guarantee that the system is asymptotically stable. Numerical simulations are investigated to verify the effectiveness of the proposed AFSMC scheme.

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References

  1. Park, R.: Adaptive control strategies for MEMS Gyroscopes. PhD Dissertation, UC Berkeley (2000)

  2. Leland, P.: Adaptive control of a MEMS gyroscope using Lyapunov methods. IEEE Trans. Control Syst. Technol. 14(2), 278–283 (2006)

    Article  Google Scholar 

  3. John, J., Vinay, T.: Novel concept of a single mass adaptively controlled triaxial angular rate sensor. IEEE Sens. J. 6(3), 588–595 (2006)

    Article  Google Scholar 

  4. Batur, C., Sreeramreddy, T.: Sliding mode control of a simulated MEMS gyroscope. ISA Trans. 45(1), 99–108 (2006)

    Article  Google Scholar 

  5. Sung, W., Lee, Y.: On the mode-matched control of MEMS vibratory gyroscope via phase-domain analysis and design. IEEE/ASME Trans. Mechatron. 14(4), 446–455 (2009)

    Article  MathSciNet  Google Scholar 

  6. Fei, J.: Robust adaptive vibration tracking control for a MEMS vibratory gyroscope with bound estimation. IET Control Theory Appl. 4(6), 1019–1026 (2010)

    Article  Google Scholar 

  7. Park, S., Horowitz, R., Hong, S., Nam, Y.: Trajectory-switching algorithm for a MEMS gyroscope. IEEE Trans. Instrum. Meas. 56(60), 2561–2569 (2007)

    Article  Google Scholar 

  8. Sadati, N., Ghadami, R.: Adaptive multi-model sliding mode control of robotic manipulators using soft computing. Neurocomputing 71(2), 2702–2710 (2008)

    Article  Google Scholar 

  9. Park, B.S., Yoo, S.J., Park, J.B., Choi, Y.H.: Adaptive neural sliding mode control of nonholonomic wheeled mobile robots with model uncertainty. IEEE Trans. Control Syst. Technol. 17(1), 207–214 (2009)

    Article  Google Scholar 

  10. Lee, M., Choi, Y.: An adaptive neucontroller using RBFN for robot manipulators. IEEE Trans. Ind. Electron. 51(3), 711–717 (2004)

    Article  Google Scholar 

  11. Wang, L.: Adaptive Fuzzy Systems and Control-Design and Stability Analysis. Prentice Hall, New Jersey (1994)

    Google Scholar 

  12. Guo, Y., Woo, P.: An adaptive fuzzy sliding mode controller for robotic manipulators. IEEE Trans. Syst. Man Cybern., Part A, Syst. Hum. 33(2), 149–159 (2004)

    Google Scholar 

  13. Yoo, B., Ham, W.: Adaptive control of robot manipulator using fuzzy compensator. IEEE Trans. Fuzzy Syst. 8(2), 186–199 (2000)

    Article  Google Scholar 

  14. Wai, R.J.: Fuzzy sliding-mode control using adaptive tuning technique. IEEE Trans. Ind. Electron. 54(1), 586–594 (2007)

    Article  Google Scholar 

  15. Wai, R.J., Lin, C.M., Hsu, C.F.: Adaptive fuzzy sliding-mode control for electrical servo drive. Fuzzy Sets Syst. 143(2), 295–310 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  16. Chen, B., Liu, X.S., Tong, C.: Adaptive fuzzy output tracking control of MIMO nonlinear uncertain systems. IEEE Trans. Fuzzy Syst. 15(2), 287–300 (2007)

    Article  Google Scholar 

  17. Ren, C., Tong, S., Li, Y.: Fuzzy adaptive high-gain-based observer backstepping control for SISO nonlinear systems with dynamical uncertainties. Nonlinear Dyn. 67(2), 941–955 (2012)

    Article  MATH  Google Scholar 

  18. Cetin, S., Zergeroglu, E., Sivrioglu, S., Yuksek, I.: A new semiactive nonlinear adaptive controller for structures using MR damper: design and experimental validation. Nonlinear Dyn. 66(4), 731–743 (2011)

    Article  MathSciNet  Google Scholar 

  19. Li, T., Wang, D., Chen, N.: Adaptive fuzzy control of uncertain MIMO non-linear systems in block-triangular forms. Nonlinear Dyn. 63(1–2), 105–123 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  20. Wen, G., Liu, Y.: Adaptive fuzzy-neural tracking control for uncertain nonlinear discrete-time systems in the NARMAX form. Nonlinear Dyn. 66(4), 745–753 (2011)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The authors thank to the anonymous reviewers for useful comments that improved the quality of the manuscript. This work is supported by National Science Foundation of China under Grant No. 61074056, The Natural Science Foundation of Jiangsu Province under Grant No. BK2010201, and Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry.

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  1. Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology, College of Computer and Information, Hohai University, Changzhou, 213022, China

    Juntao Fei & Mingyuan Xin

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  1. Juntao Fei
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  2. Mingyuan Xin
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Correspondence to Juntao Fei.

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Fei, J., Xin, M. An adaptive fuzzy sliding mode controller for MEMS triaxial gyroscope with angular velocity estimation. Nonlinear Dyn 70, 97–109 (2012). https://doi.org/10.1007/s11071-012-0433-z

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