Integrated model reference adaptive control and time-varying angular rate estimation for micro-machined gyroscopes

Tsai, Nan-Chyuan; Sue, Chung-Yang

doi:10.1080/00207170903137034

Cited by 22 publications

(13 citation statements)

References 18 publications

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“…Furthermore, on-line estimation of the time-varying angular rate is one of the major control problems associated with MEMS gyroscopes. In the literature, there exists only three past works that considered estimation of time-varying angular rate [22][23][24] aside from our work. In [22], an adaptive controller for angular rate sensing was developed under the assumption that the time-varying angular rate can be approximated by a polynomial function in a finite time interval.…”

Section: Introductionmentioning

confidence: 96%

“…In [22], an adaptive controller for angular rate sensing was developed under the assumption that the time-varying angular rate can be approximated by a polynomial function in a finite time interval. In [23,24], the time-varying angular rate was assumed to be a pure sinusoidal. This is a very restrictive assumption that reduces the application of the estimators designed in [23,24].…”

Section: Introductionmentioning

confidence: 99%

“…In [23,24], the time-varying angular rate was assumed to be a pure sinusoidal. This is a very restrictive assumption that reduces the application of the estimators designed in [23,24]. Our work relaxed the restrictive assumptions of pure sinusoidal timevarying angular rate polynomial function approximated.…”

Section: Introductionmentioning

confidence: 99%

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Sensing of the time-varying angular rate for MEMS Z-axis gyroscopes

et al. 2010

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a b s t r a c tIn this paper, a nonlinear estimation strategy for sensing the time-varying angular rate of a Z-axis MEMS gyroscope is presented. An off-line adaptive least-squares estimation strategy is first developed to accurately estimate the unknown model parameters. Both axes of a Z-axis MEMS gyroscope are then actively controlled utilizing an on-line controller/observer to facilitate time-varying angular rate sensing. The proposed nonlinear estimation strategy is developed based on a Lyapunov-based analysis, which proves that the time-varying angular rate experienced by the device can be estimated accurately. Two cases for angular rate are investigated which are time-varying and constant magnitudes. An adaptive controller/observer was also utilized for sensing the angular rate to investigate the performance of the proposed controller/observer. Representative numerical results are discussed to demonstrate the performance of the proposed nonlinear strategy in accurately sensing the applied angular rate. Overall, the proposed nonlinear controller/observer improves sensing the constant angular rate by 50% and the time-varying angular rate by 90% when compared with an adaptive controller/observer.

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Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Sensing of the time-varying angular rate for MEMS Z-axis gyroscopes

et al. 2010

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“…Robust adaptive controller has been developed using adaptive sliding mode control to control the vibration of MEMS gyroscope [4]. Tsai and Sue [5] proposed integrated model reference adaptive control and time-varying angular rate estimation algorithm for micromachined gyroscopes. Raman et al [6] developed a closed-loop digitally controlled MEMS gyroscope using unconstrained sigma-delta force balanced feedback control.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation

Yang

Fei

2014

Journal of Applied Mathematics

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An adaptive sliding controller using radial basis function (RBF) network to approximate the unknown system dynamics microelectromechanical systems (MEMS) gyroscope sensor is proposed. Neural controller is proposed to approximate the unknown system model and sliding controller is employed to eliminate the approximation error and attenuate the model uncertainties and external disturbances. Online neural network (NN) weight tuning algorithms, including correction terms, are designed based on Lyapunov stability theory, which can guarantee bounded tracking errors as well as bounded NN weights. The tracking error bound can be made arbitrarily small by increasing a certain feedback gain. Numerical simulation for a MEMS angular velocity sensor is investigated to verify the effectiveness of the proposed adaptive neural control scheme and demonstrate the satisfactory tracking performance and robustness.

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“…Raman et al [6] proposed a closed-loop digitally controlled MEMS gyroscope using unconstrained sigma-delta force balanced feedback control. Tsai and Sue [7] developed integrated model reference adaptive control and time-varying angular rate estimator for microgyroscopes.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Control of MEMS Gyroscope Based on Global Terminal Sliding Mode Controller

Yan

Fei

2013

Mathematical Problems in Engineering

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An adaptive global fast terminal sliding mode control (GFTSM) is proposed for tracking control of Micro-Electro-Mechanical Systems (MEMS) vibratory gyroscopes under unknown model uncertainties and external disturbances. To improve the convergence rate of reaching the sliding surface, a global fast terminal sliding surface is employed which can integrate the advantages of traditional sliding mode control and terminal sliding mode control. It can be guaranteed that sliding surface and equilibrium point can be reached in a shorter finite time from any initial state. In the presence of unknown upper bound of system nonlinearities, an adaptive global fast terminal sliding mode controller is derived to estimate this unknown upper bound. Simulation results demonstrate that the tracking error can be attenuated efficiently and robustness of the control system can be improved with the proposed adaptive global fast terminal sliding mode control.

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Integrated model reference adaptive control and time-varying angular rate estimation for micro-machined gyroscopes

Cited by 22 publications

References 18 publications

Sensing of the time-varying angular rate for MEMS Z-axis gyroscopes

Sensing of the time-varying angular rate for MEMS Z-axis gyroscopes

Adaptive Sliding Mode Control of MEMS Gyroscope Based on Neural Network Approximation

Adaptive Control of MEMS Gyroscope Based on Global Terminal Sliding Mode Controller

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