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Research Papers

Adaptive Fuzzy Sliding Mode Control of MEMS Gyroscope Sensor Using Fuzzy Switching Approach

[+] Author and Article Information
Juntao Fei

Jiangsu Key Laboratory of Power Transmission
and Distribution Equipment Technology,
College of Computer and Information,
Hohai University,
Changzhou 213022, China
e-mail: jtfei@yahoo.com

Mingyuan Xin

Jiangsu Key Laboratory of Power Transmission
and Distribution Equipment Technology,
College of Computer and Information,
Hohai University,
Changzhou 213022, China

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received July 20, 2012; final manuscript received August 9, 2014; published online December 10, 2014. Assoc. Editor: May-Win L. Thein.

J. Dyn. Sys., Meas., Control 137(5), 051002 (May 01, 2015) (7 pages) Paper No: DS-12-1229; doi: 10.1115/1.4028812 History: Received July 20, 2012; Revised August 09, 2014; Online December 10, 2014

In this paper, an adaptive fuzzy sliding mode control strategy, which combines the merits of sliding mode control and adaptive fuzzy control, is proposed to control the MEMS gyroscope in the presence of model uncertainties and external disturbances. The adaptive fuzzy systems are employed to approximate both the equivalent control term and the sliding mode controller. Then the switching control becomes continuous and the chattering phenomena can be attenuated. The adaptation laws based on the Lyapunov analysis can adaptively adjust the fuzzy rules to guarantee the asymptotical stability of the adaptive fuzzy closed-loop control system. Numerical simulations are investigated to verify the effectiveness of the proposed adaptive fuzzy control schemes.

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Figures

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Fig. 1

Schematic structure of a z-axis MEMS gyroscope in x–y plane

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Fig. 2

Block diagram of adaptive fuzzy sliding mode control system

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Fig. 3

Position tracking using conventional sliding mode control

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Fig. 4

Tracking error using conventional sliding mode control

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Fig. 5

Sliding surface s using conventional sliding mode control

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Fig. 6

Control efforts using conventional sliding mode control

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Fig. 7

Position tracking using adaptive fuzzy sliding mode control

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Fig. 8

Tracking error using adaptive fuzzy sliding mode control

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Fig. 9

Sliding surface s using adaptive fuzzy sliding mode control

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Fig. 10

Control efforts using adaptive fuzzy sliding mode control

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Fig. 11

Position tracking using conventional sliding mode control under large disturbance

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Fig. 12

Position tracking using adaptive fuzzy sliding mode control under large disturbance

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