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Vol. 141, No. 6, June 2012, pp. 92-105




Intelligent Robust Nonlinear Controller for MEMS Angular Rate Sensor


1 Mohammad-Reza Moghanni-Bavil-Olyaei, 2 Ahmad Ghanbari, 3Jafar Keighobadi

1,2,3 Faculty of Mech. Eng., University of Tabriz, 29 Bahman, Tabriz, P.C. 51666-14761, Iran

2 Center of Excellence for Mechatronics Research Lab., School of Engineering Emerging Technologies, University of Tabriz, Tabriz, Iran

Tel.: 1 +98 914 101 8544, 2 +98 914 116 0796

E-mail: 1 Mr_moghanni88@ms.tabrizu.ac.ir, 2 a-ghanbari@tabrizu.ac.ir


Received: 12 March 2012   /Accepted: 25 June 2012   /Published: 30 June 2012


Digital Sensors and Sensor Sysstems


Abstract: This paper presents a control strategy for micro-electro-mechanical systems (MEMS) z-axis gyroscope, based on the coupling of the fuzzy logic control with the so-called sliding mode control (SMC) approach. An adaptive model reference state tracking controller which can estimate the angular velocity vector, and the damping and stiffness model coefficients in real-time is proposed. The motivation for using SMC in MEMS mainly relies on its appreciable features, such as design simplicity and robustness. The tracking performance of pure adaptive SMC is affected by high range chattering due to modeling uncertainties and exogenous inputs. In this paper, this problem is suitably circumvented by adopting an adaptive fuzzy sliding mode control (AFSMC) approach which results in chattering free tracking and improved estimation accuracy. For this proposed approach, we have used a fuzzy logic control to generate the reaching control signal. Therefore, the simple and intelligent Mamdani-type controller is resulted with high robustness against parametric uncertainties and exogenous disturbances. The stability of the system is guaranteed in the sense of the Lyapunov stability theorem. Numerical simulations using the nonlinear dynamic model of a MEMS z-axis gyroscope with uncertainties show the effectiveness of the approach in trajectory tracking problems and robustness in estimating the gyroscope parameters and also the angular velocity. The simulation results that are compared with the results of conventional adaptive SMC indicate that the control performance of the gyroscope system is satisfactory and the proposed AFSMC can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances.


Keywords: Fuzzy control, Adaptive control, Sliding mode control, Chattering, MEMS gyroscope



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