A new hybrid robust control of MEMS gyroscope

Abstract

To control microelectromechanical systems (MEMS) gyroscope axis, we propose and investigate a new robust sliding mode controller (NRSMC). The sliding surface in the phase space converges to the equilibrium point within a finite period from any initial state. However, the main drawback of this control system is the chattering phenomenon, which is undesirable for the MEMS system. To solve this problem, we suggest a novel hybrid control system which improves trajectory tracking and eliminates the chattering. The dynamic stability of NRSMC against external disturbances is proved by applying the Lyapunov theory. The effectiveness of the proposed control method is verified by numerical simulation with a random noise applied to demonstrate the robustness of the proposed control system.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  1. Asad YP, Shamsi A, Tavoosi J (2017) Backstepping-based recurrent type-2 fuzzy sliding mode control for MIMO systems (MEMS triaxial gyroscope case study). Int J Uncertain Fuzziness Knowl Based Syst 25(02):213–233

    MathSciNet  Article  Google Scholar 

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

    Article  Google Scholar 

  3. Chu Y, Fei J (2015) Adaptive global sliding mode control for MEMS gyroscope using RBF neural network. Math Probl Eng 2015:1–9

    MathSciNet  MATH  Google Scholar 

  4. Chu Y, Fang Y, Fei J (2017) Adaptive neural dynamic global PID sliding mode control for MEMS gyroscope. Int J Mach Learn Cybern 8(5):1707–1718

    Article  Google Scholar 

  5. Fei J, Yang Y (2016) Robust neural network control of MEMS gyroscope using adaptive sliding mode compensator. Robotica 34(3):497–512

    Article  Google Scholar 

  6. Fei J, Yuan Z (2013) Dynamic sliding mode control of MEMS gyroscope. In: 2013 IEEE international conference on control applications. IEEE, pp 437–442

  7. Fei J, Yan W, Yang Y (2015) Adaptive nonsingular terminal sliding mode control of MEMS gyroscope based on backstepping design. Int J Adapt Control Signal Process 29(9):1099–1115

    MathSciNet  Article  Google Scholar 

  8. Ghanbari A, Moghanni-Bavil-Olyaei MR (2014) Adaptive fuzzy terminal sliding-mode control of MEMS z-axis gyroscope with extended Kalman filter observer. Syst Sci Control Eng Open Access J 2(1):183–191

    Article  Google Scholar 

  9. Rahmani M (2017) MEMS gyroscope control using a novel compound robust control. ISA Trans 5:6. https://doi.org/10.1016/j.isatra.2017.11.009i

    Article  Google Scholar 

  10. Rahmani M (2019) Control of a caterpillar robot manipulator using hybrid control. Microsyst Technol 25(7):2841–2854

    Article  Google Scholar 

  11. Rahmani M, Rahman MH (2019a) A novel compound fast fractional integral sliding mode control and adaptive PI control of a MEMS gyroscope. Microsyst Technol. https://doi.org/10.1007/s00542-018-4284-5

    Article  Google Scholar 

  12. Rahmani M, Rahman MH (2019b) An upper-limb exoskeleton robot control using a novel fast fuzzy sliding mode control. J Intell Fuzzy Syst 36(3):2581–2592

    Article  Google Scholar 

  13. Rahmani M, Rahman MH (2019c) A new adaptive fractional sliding mode control of a MEMS gyroscope. Microsyst Technol 25(9):3409–3416

    Article  Google Scholar 

  14. Rahmani M, Ghanbari A, Ettefagh MM (2016a) Hybrid neural network fraction integral terminal sliding mode control of an Inchworm robot manipulator. Mech Syst Signal Process 80:117–136

    Article  Google Scholar 

  15. Rahmani M, Ghanbari A, Ettefagh MM (2016b) Robust adaptive control of a bio-inspired robot manipulator using bat algorithm. Expert Syst Appl 56:164–176

    Article  Google Scholar 

  16. Rahmani M, Komijani H, Ghanbari A, Ettefagh MM (2018a) Optimal novel super-twisting PID sliding mode control of a MEMS gyroscope based on multi-objective bat algorithm. Microsyst Technol 24(6):2835–2846

    Article  Google Scholar 

  17. Rahmani M, Ghanbari A, Ettefagh MM (2018b) A novel adaptive neural network integral sliding-mode control of a biped robot using bat algorithm. J Vib Control 24(10):2045–2060

    MathSciNet  Article  Google Scholar 

  18. Rahmani M, Rahman MH, Ghommam J (2019) A 7-DoF upper limb exoskeleton robot control using a new robust hybrid controller. Int J Control Autom Syst 17(4):986–994

    Article  Google Scholar 

  19. Ren J, Zhang R, Xu B (2016) Adaptive fuzzy sliding mode control of MEMS gyroscope with finite time convergence. J Sens 2016(5):1–7

    Article  Google Scholar 

  20. Saxena S, Sharma R, Pant BD (2017) Design and development of guided four beam cantilever type MEMS based piezoelectric energy harvester. Microsyst Technol 23(6):1751–1759

    Article  Google Scholar 

  21. Utkin V, Lee H (2006) Chattering problem in sliding mode control systems. In: International workshop on variable structure systems. VSS’06. IEEE, pp 346–350

  22. Wang S, Fei J (2014) Robust adaptive sliding mode control of MEMS gyroscope using T-S fuzzy model. Nonlinear Dyn 77(1–2):361–371

    MathSciNet  Article  Google Scholar 

  23. Wang X, Xu XB, Zhang DW, Wu XZ (2018) Pre-buried mask wet etching for suspended silicon microstructures applied in rocking mass micro-gyroscope. Microsyst Technol 24(2):1081–1087

    Article  Google Scholar 

  24. Xin M, Fei J (2015) Adaptive vibration control for MEMS vibratory gyroscope using backstepping sliding mode control. J Vib Control 21(4):808–817

    MathSciNet  Article  Google Scholar 

  25. Yan W, Hou S, Fang Y, Fei J (2017) Robust adaptive nonsingular terminal sliding mode control of MEMS gyroscope using fuzzy-neural-network compensator. Int J Mach Learn Cybern 8(4):1287–1299

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Mehran Rahmani.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rahmani, M., Rahman, M.H. & Nosonovsky, M. A new hybrid robust control of MEMS gyroscope. Microsyst Technol 26, 853–860 (2020). https://doi.org/10.1007/s00542-019-04584-z

Download citation