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Finite-Time Composite Adaptive Fuzzy Control of Permanent Magnet Synchronous Motors

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Abstract

In this paper, a finite-time composite adaptive fuzzy control approach is proposed for position tracking of permanent magnet synchronous motors (PMSMs) with uncertain parameters and load torque disturbances. Based on the approximate ability of fuzzy logic systems (FLSs), a novel finite-time adaptive fuzzy control is developed, where dynamic surface control with error compensation mechanism is incorporated in the control design. A serial-parallel estimation model of PMSM is established. The prediction error between PMSM and the serial-parallel estimation model is utilized to construct the adaptive law of FLSs, which can improve the approximate accuracy of FLSs. Moreover, by introducing a new fuzzy adaptive law, the algebraic loop problem in the existing backstepping based control approaches is overcome. It is proven that all signals of closed-loop systems are uniformly ultimately bounded, and the position tracking error can converge to a small neighborhood of the origin in finite time. Finally, the simulation results are presented to show the effectiveness of the proposed control approach, and some comparisons are given to show the rapid and accurate position tracking performance.

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References

  1. Bae, B., Sul, S.K., Kwon, J.H., Byeon, J.S.: Implementation of sensorless vector control for super-high-speed PMSM of turbo-compressor. IEEE Trans. Ind. Appl. 39(3), 811–818 (2003)

    Article  Google Scholar 

  2. Preindl, M., Bolognani, S.: Model predictive direct torque control with finite control set for PMSM drive systems, Part 1: Maximum torque perampere operation. IEEE Trans. Ind. Inf. 9(4), 1912–1921 (2013)

    Article  Google Scholar 

  3. Sangsefidi, Y., Ziaeinejad, S., Mehrizi-Sani, A., Pairodin-Nabi, H., Shoulaie, A.: Estimation of stator resistance in direct torque control synchronous motor drives. IEEE Trans. Energy Convers. 30(2), 626–634 (2015)

    Article  Google Scholar 

  4. Zhang, X., Sun, L., Zhao, K., Sun, L.: Nonlinear speed control for PMSM system using sliding-mode control and disturbance compensation techniques. IEEE Trans. Power Electron. 28(3), 1358–1365 (2013)

    Article  Google Scholar 

  5. Feng, Y., Zheng, J.F., Yu, X.H., Truong, N.V.: Hybrid terminal sliding-mode observer design method for a permanent magnet synchronous motor control system. IEEE Trans. Ind. Electron. 56(9), 3424–3431 (2009)

    Article  Google Scholar 

  6. Liu, X.D., Yu, H.S., Yu, J.P., Zhao, L.: Combined speed and current terminal sliding mode control with nonlinear disturbance observer for PMSM drive. IEEE Access 6, 29594–29601 (2018)

    Article  Google Scholar 

  7. Hsien, Y.Y., Sun, Y.Y., Tsai, M.C.: H\(\infty \) control for a sensorless permanent magnet synchronous drive. IEE Proc. Electric Power Appl. 144(3), 173–181 (1997)

    Article  Google Scholar 

  8. Lee, T.S., Lin, C.H., Lin, F.J.: An adaptive H\(\infty \) control design for permanent magnet synchronous motor drives. Control. Eng. Pract. 13(4), 425–439 (2005)

    Article  Google Scholar 

  9. Tursini, M., Parasiliti, F., Zhang, D.Q.: Real-time gain tuning of PI controllers for high-performance PMSM drives. IEEE Trans. Ind. Appl. 38(4), 1018–1026 (2002)

    Article  Google Scholar 

  10. Sant, A.V., Rajagopal, K.R.: PMSM speed control using hybrid fuzzy-PI with novel switching functions. IEEE Trans. Magn. 45(10), 4672–4675 (2009)

    Article  Google Scholar 

  11. Marino, R., Peresada, S., Valigi, P.: Adaptive input-output linearization control of induction motor. IEEE Trans. Autom. Control 38(2), 208–221 (1993)

    Article  Google Scholar 

  12. Liu, Y.J., Tong, S.C.: Adaptive fuzzy control for a class of unknown nonlinear dynamical systems. Fuzzy Sets Syst. 263(15), 49–70 (2015)

    Article  MathSciNet  Google Scholar 

  13. Cui, G.Z., Yu, J.P., Wang, Q. G.: Finite-time adaptive fuzzy control for MIMO nonlinear systems with input saturation via improved command-filtered backstepping. IEEE Trans. Syst. Man Cybern. https://doi.org/10.1109/TSMC.2020.3010642

  14. Yang, C., Li, Z., Cui, R., Xu, B.: Neural network based motion control of an underactuated wheeled inverted pendulum model. IEEE Trans. Neural Netw. Learning Syst. 25(11), 2004–2016 (2017)

    Article  Google Scholar 

  15. He, W., Mu, X.X., Zhang, L., Zou, Y.: Modeling and trajectory tracking control for flapping-wing micro aerial vehicles. IEEE/CAA J. Autom. Sin. 8(1), 148–156 (2021)

    Article  MathSciNet  Google Scholar 

  16. He, W., Wang, T.T., He, X.Y., Yang, L.J., Kaynak, O.: Dynamical modeling and boundary vibration control of a rigid-flexible wing system. IEEE/ASME Trans. Mechatron. 25(6), 2711–2721 (2020)

    Article  Google Scholar 

  17. Liu, Z.J., Han, Z.J., Zhao, Z.J., He, W.: Modeling and adaptive control for a spatial flexible spacecraft with unknown actuator failures. Sci. China Inf. Sci. https://doi.org/10.1007/s11432-020-3109-x

  18. Yu, J.P., Chen, B., Yu, H.S.: Fuzzy-approximation-based adaptive control of the chaotic permanent magnet synchronous motor. Nonlinear Dyn. 69(3), 1479–1488 (2012)

    Article  MathSciNet  Google Scholar 

  19. Liu, D., Li, M.G.: Adaptive wavelet neural network backstepping sliding mode tracking control for PMSM drive system. Automatika 55(4), 405–415 (2014)

    Article  Google Scholar 

  20. Yu, J.P., Shi, P., Dong, W., Chen, B., Lin, C.: Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors. IEEE Trans. Neural Netw. Learning Syst. 26(3), 640–645 (2015)

    Article  MathSciNet  Google Scholar 

  21. Zou, M., Yu, J.P., Ma, Y.M.: Command filtering-based adaptive fuzzy control for permanent magnet synchronous motors with full state constraints. Inf. Sci. 518, 1–12 (2020)

    Article  MathSciNet  Google Scholar 

  22. Lu, S.K., Wang, X.C.: Adaptive neural network output feedback control of incommensurate fractional-order PMSMs with input saturation via command filtering and state observer. Neural Comput. Appl. https://doi.org/10.1007/s00521-020-05344-1

  23. Chang, W.M., Tong, S.C.: Adaptive fuzzy tracking control design for permanent magnet synchronous motors with output constraint. Nonlinear Dyn. 87(1), 291–302 (2017)

    Article  Google Scholar 

  24. Fu, C., Yu, J.P., Zhao, L., Yu, H.S., Lin, C., Ma, Y.M.: Barrier Lyapunov function-based adaptive fuzzy control for induction motors with iron losses and full state constraints. Neurocomputing 287(26), 208–220 (2018)

    Article  Google Scholar 

  25. Chen, Q., Ren, X., Na, J.: Robust finite-time chaos synchronization of uncertain permanent magnet synchronous motors. ISA Trans. 58, 262–269 (2015)

    Article  Google Scholar 

  26. Sun, Y., Wu, X., Bai, L., Wei, Z., G. Sun, G.: Finite-time synchronization control and parameter identification of uncertain permanent magnet synchronous motor. Neurocomputing 207(9), 511–518 (2016)

  27. Yang, X.T., Yu, J.P., Wang, Q., Zhao, L., Yu, H.S., Lin, C.: Adaptive fuzzy finite-time command filtered tracking control for permanent magnet synchronous motors. Neurocomputing 337(14), 110–119 (2019)

    Article  Google Scholar 

  28. Lu, S.K., Wang, X.C., Wang, L.D.: Finite-time adaptive neural network control for fractional-order chaotic PMSM via command filtered backstepping. Adv. Differ. Eqn. 2020(1), 121–141 (2020)

    Article  MathSciNet  Google Scholar 

  29. Cheng, S., Yu, J.P., Lin, C., Zhao, L., Ma, Y.M.: Neuro adaptive finite-time output feedback control for PMSM stochastic nonlinear systems with iron losses via dynamic surface technique. Neurocomputing 402(10), 162–170 (2020)

    Article  Google Scholar 

  30. Luo, H.J., Yu, J.P., Lin, C., Liu, Z.J., Zhao, L., Ma, Y.M.: Finite-time dynamic surface control for induction motors with input saturation in electric vehicle drive systems. Neurocomputing 369(12), 166–175 (2019)

    Article  Google Scholar 

  31. Tong, S.C., Li, Y.M., Sui, S.: Adaptive fuzzy tracking control design for SISO uncertain nonstrict feedback nonlinear systems. IEEE Trans. Fuzzy Syst. 24(6), 1441–1454 (2016)

    Article  Google Scholar 

  32. Cui, G.Z., Yu, J.P., Shi, P.: Observer-based finite-time adaptive fuzzy control with prescribed performance for nonstrict-feedback nonlinear systems. IEEE Trans. Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2020.3048518

  33. Wang, L.X.: Adaptive Fuzzy Systems and Control. Prentice Hall, Englewood Cliffs, NJ (1994)

    Google Scholar 

  34. Haimo, V.T.: Finite time controllers. SIAM J. Control. Optim. 24(4), 760–770 (1986)

    Article  MathSciNet  Google Scholar 

  35. Bhat, S.P., Bernstein, D.S.: Finite-time stability of continuous autonomous systems. SIAM J. Control. Optim. 38(3), 751–766 (2000)

    Article  MathSciNet  Google Scholar 

  36. Chen, B., Wang, F., Liu, X.P., Lin, C.: Finite-time adaptive fuzzy tracking control design for nonlinear systems. IEEE Trans. Fuzzy Syst. 26(3), 1209–1216 (2018)

    Google Scholar 

  37. Xu, B., Shi, Z.K., Yang, C.G., Sun, F.C.: Composite neural dynamic surface control of a class of uncertain nonlinear systems in strict-feedback form. IEEE Trans. Cybern. 44(12), 2626–2634 (2014)

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 61603165, and the Natural Science Foundation of Liaoning Province (2019-BS-119).

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Authors and Affiliations

  1. School of Electrical Engineering, Liaoning University of Technology, Jinzhou, China

    Yang Yu, Lusong Ding & Wei Wang

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  1. Yang Yu
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  2. Lusong Ding
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  3. Wei Wang
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Correspondence to Wei Wang.

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Yu, Y., Ding, L. & Wang, W. Finite-Time Composite Adaptive Fuzzy Control of Permanent Magnet Synchronous Motors. Int. J. Fuzzy Syst. 24, 135–146 (2022). https://doi.org/10.1007/s40815-021-01113-x

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  • DOI: https://doi.org/10.1007/s40815-021-01113-x

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