System Dynamics and Adaptive Control of MEMS Gyroscope Sensor

Fei, Juntao; Dai, Weili; Hua, Min; Xue, Yuncan

doi:10.3182/20110828-6-it-1002.00034

Cited by 5 publications

(4 citation statements)

References 16 publications

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“…Note that the damping coefficient x y d and the stiffness coefficient xy k have been considered to model the coupling effect between x and y directions, which are mainly caused by fabrication imperfections (Fei & Ding 2010 models, finite impulse response and etc. Here we use statespace model which is a suitable tool for description and handling of MIMO systems.…”

Section: Dynamics Of Mems Vibratory Rate Gyroscopementioning

confidence: 99%

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Model Predictive Control of MEMS Vibratory Gyroscope

Pishrobat

Keighobadi

2014

IFAC Proceedings Volumes

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Section: Dynamics Of Mems Vibratory Rate Gyroscopementioning

confidence: 99%

“…Without any constraint, the unknown vector η can be found by minimizing the cost function J: (Fei & Ding 2010):…”

Section: Prediction and Optimization Using Laguerre Functionsmentioning

confidence: 99%

Model Predictive Control of MEMS Vibratory Gyroscope

Pishrobat

Keighobadi

2014

IFAC Proceedings Volumes

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“…Thus, analyzing both characteristics of the structure together as a system model is important and necessary for efficient optimization. Therefore, equivalent circuit models have been suggested to represent the dynamics of MEMS devices [14,15,16,17] and are integrated into commercial software, namely, MATLAB Simulink (Natick, MA, USA) [18,19]. To consider the thermal or other environmental factors, the finite-element model of a MEMS device is often used, which is characterized by its dynamic flexibility [20,21].…”

Section: Introductionmentioning

confidence: 99%

System Modeling of a MEMS Vibratory Gyroscope and Integration to Circuit Simulation

Kwon

Seok

Lim

2017

Sensors

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Recently, consumer applications have dramatically created the demand for low-cost and compact gyroscopes. Therefore, on the basis of microelectromechanical systems (MEMS) technology, many gyroscopes have been developed and successfully commercialized. A MEMS gyroscope consists of a MEMS device and an electrical circuit for self-oscillation and angular-rate detection. Since the MEMS device and circuit are interactively related, the entire system should be analyzed together to design or test the gyroscope. In this study, a MEMS vibratory gyroscope is analyzed based on the system dynamic modeling; thus, it can be mathematically expressed and integrated into a circuit simulator. A behavioral simulation of the entire system was conducted to prove the self-oscillation and angular-rate detection and to determine the circuit parameters to be optimized. From the simulation, the operating characteristic according to the vacuum pressure and scale factor was obtained, which indicated similar trends compared with those of the experimental results. The simulation method presented in this paper can be generalized to a wide range of MEMS devices.

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“…Its theory is quite simple: the sensor determines how much the orientation over a segment has changed. Once it calculates this parameter, it measures the angular velocity (degrees per second), from which calculates angular shift [7,8].…”

Section: Mathematical Modelling Of a Two Degree Of Freedom Platform Umentioning

confidence: 99%

Mathematical Modelling of a Two Degree of Freedom Platform Using Accelerometers and Gyro Sensors

Lage¹,

Segundo²,

Pinto³

2016

JMEA

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This paper demonstrates the assembly of a servo-controlled platform with two degrees of freedom, empirical methods and a developed closed-loop control found in the system mathematical model. This control aims to stabilize and hold small objects on the platform. We parsed the step response in X and Y axes, hence we found the first and second-order models for each one. We did some further analyses to decide which one would better represent the behavior of the system. The MATLAB software provided step response for the model empirically obtained and latter compared it to experimental data acquired in the trials. Accelerometers and gyro sensors from the MPU-6050 sensor measured the angular position of platform on X and Y axes. In order to improve measurements accuracy and eliminate noise effects, we implemented the complementary filter to the firmware system. We used Arduino to control servomotors through PWM pulses and perform data acquisition.

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System Dynamics and Adaptive Control of MEMS Gyroscope Sensor

Cited by 5 publications

References 16 publications

Model Predictive Control of MEMS Vibratory Gyroscope

Model Predictive Control of MEMS Vibratory Gyroscope

System Modeling of a MEMS Vibratory Gyroscope and Integration to Circuit Simulation

Mathematical Modelling of a Two Degree of Freedom Platform Using Accelerometers and Gyro Sensors

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