Design of an Adaptive Fuzzy Sliding Mode Control Using Supervisory Fuzzy Control for Micro-Electro-Mechanical Systems (MEMS) Z-Axis Gyroscope. Issue 2 (June 2014)

• Record Type: Journal Article
• Authors: Moghanni-Bavil-Olyaei, M. R.; Ghanbari, A.
• Is Part Of: Journal of low frequency noise, vibration, and active control. Volume 33:Issue 2(2014)
• Page Start: 163
• Page End: 187
• Publication Date: 2014-06
• Subjects: Fuzzy Control -- MEMS Gyroscope -- Sliding Mode Control -- Lyapunov Method -- Uncertainties; Vibration -- Periodicals; Noise -- Periodicals; Sound -- Periodicals; Damping (Mechanics) -- Periodicals; Damping (Mechanics); Noise; Sound; Vibration; Periodicals; 620.205
• DOI: 10.1260/0263-0923.33.2.163
• Languages: English
• ISSNs: 1461-3484

Abstract

This paper presents a novel robust adaptive control strategy for MEMS gyroscope, based on the coupling of the fuzzy logic control with sliding mode control (SMC) approach and adaptive laws. The drawbacks of the conventional SMC include chattering phenomenon and requirement of a priori knowledge of the bounds of uncertainties. In this paper, these problems are suitably attenuated by adopting an adaptive fuzzy sliding mode control (AFSMC) approach which uses two additional fuzzy self-tuning controllers as supervisory fuzzy systems to adaptively tune the output control gain, sliding gain of the AFSMC in order to speed up the convergence rates of the tracking errors and parameter estimations with a desired level of attenuation. Control system stability is proved by Lyapunov method. Numerical simulations using the MEMS gyroscope model with uncertainties demonstrate the effectiveness of this approach in high speed trajectory tracking problems and robustness in estimating the gyroscope parameters and the angular velocity. Numerical simulations show that the chattering is effectively attenuated by this method. Convergence rate of tracking errors and the gyroscope parameters is better than convergence rates in the literature.