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Journal of Mechanical Science and Technology

, Volume 32, Issue 2, pp 793–798 | Cite as

Full-state-feedback, Fuzzy type I and Fuzzy type II control of MEMS accelerometer

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Abstract

This paper presents classic and knowledge-based intelligent controllers for regulation of a vibratory MEMS accelerometer. The proposed methods comprise Fuzzy type I (FTI), Fuzzy type II (FTII) and Full-state-feedback (FSF) control systems. An ideal model of sensor under FSF controller is used to generate the required reference data to train if-then rule-base and Membership functions (MFs) of both fuzzy controllers. Through feeding the reference data as well as the FTI/FTII output into an Adaptive neural fuzzy inference system (ANFIS), the rules and MFs of the FTI/FTII system are updated. The control systems are realized by adding a Kalman filter (KF) loop to the force-balancing method for estimation of state variables and input acceleration. Stochastic noises are filtered out while keeping good tracking performance of MEMS accelerometer and reducing the displacement of the mass under the closed-loop ANFIS-KF structure.

Keywords

MEMS accelerometer Fuzzy type II Full state feedback ANFIS Force-balancing Extended Kalman filter 

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References

  1. [1]
    J. Lee et al., High-shock silicon accelerometer with an overrange stopper, J. Mech. Sci. Technol., 30 (2016) 1817, https://doi.org/10.1007/s12206-016-0338-8.CrossRefGoogle Scholar
  2. [2]
    J. Wu, Sensing and control electronics for low-mass lowcapacitance MEMS accelerometer, Carnegie Institute of Technology (2002).Google Scholar
  3. [3]
    P. M. Hosseini and J. Keighobadi, Force-balancing model predictive control of MEMS vibratory gyroscope sensor, Proceedings of the Institution of Mechanical Engineers, Part C: J. of Mechanical Engineering Science, 230 (17) (2016) 3055–3065.Google Scholar
  4. [4]
    J. Keighobadi and M. J. Yarmohammadi, New chatter-free sliding mode synchronization of steer-by-wire systems under chaotic conditions, J. of Mech. Sci. Technol., 30 (2016) 3829, https://doi.org/10.1007/s12206-016-0746-9.CrossRefGoogle Scholar
  5. [5]
    K. L. Chau et al., An integrated force-balanced capacitive accelerometer for low-g applications, Sensors and Actuators A: Physical, 54 (1–3) (1996) 472–476.CrossRefGoogle Scholar
  6. [6]
    C. H. Liu and T. W. Kenny, A high-precision, widebandwidth micromachined tunneling accelerometer, J. of Microelectromechanical Systems, 10 (3) (2001) 425–433.CrossRefGoogle Scholar
  7. [7]
    E. Sarraf, B. Cousins, E. Cretu and S. Mirabbasi, Design and implementation of a novel sliding mode sensing architecture for capacitive MEMS accelerometers, J. of Micromechanics and Microengineering, 21 (11) (2011) 115033.CrossRefGoogle Scholar
  8. [8]
    L. Zhang, J. Liu, J. Lai and Z. Xiong, Performance analysis of adaptive neuro fuzzy inference system control for MEMS navigation system, Mathematical Problems in Engineering, 2014 (2014) 1–7.Google Scholar
  9. [9]
    L. Dong and K. Zhang, Sensing and control of MEMS Accelerometers using KF, Control and Decision Conference (CCDC), 2012 24th Chinese: IEEE (2012) 3074–3079.CrossRefGoogle Scholar
  10. [10]
    J. Keighobadi and M. B. Menhaj, From nonlinear to fuzzy approaches in trajectory tracking control of wheeled mobile robots, Asian J. of Control, 14 (4) (2012) 960–973.MathSciNetCrossRefMATHGoogle Scholar
  11. [11]
    J. R. Castro, O. Castillo, P. Melin and A. Rodríguez-Díaz, A hybrid learning algorithm for a class of interval type-2 fuzzy neural networks, Information Sciences, 179 (2009) 2175–2193.CrossRefMATHGoogle Scholar
  12. [12]
    J. Tavoosi, A. A. Suratgar and M. B. Menhaj, Stable ANFIS2 for nonlinear system identification, Neurocomputing, 182 (2016) 235–246.CrossRefGoogle Scholar
  13. [13]
    O. Castillo, P. Melin, J. Kacprzyk and W. Pedrycz, Type-2 fuzzy logic: Theory and applications, IEEE Granular Computing Conference, Fremont, CA, USA (2007) 145–145.Google Scholar

Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringUniversity of TabrizTabrizIran

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