Microelectromechanical Systems Gyroscope Research Articles

Vision sensor and dual MEMS gyroscope integrated system for attitude determination on moving base.

To determine the relative attitude between the objects on a moving base and the base reference system by a MEMS (Micro-Electro-Mechanical Systems) gyroscope, the motion information of the base is redundant, which must be removed from the gyroscope. Our strategy is to add an auxiliary gyroscope attached to the reference system. The master gyroscope is to sense the total motion, and the auxiliary gyroscope is to sense the motion of the moving base. By a generalized difference method, relative attitude in a non-inertial frame can be determined by dual gyroscopes. With the vision sensor suppressing accumulative drift of the MEMS gyroscope, the vision and dual MEMS gyroscope integration system is formed. Coordinate system definitions and spatial transform are executed in order to fuse inertial and visual data from different coordinate systems together. And a nonlinear filter algorithm, Cubature Kalman filter, is used to fuse slow visual data and fast inertial data together. A practical experimental setup is built up and used to validate feasibility and effectiveness of our proposed attitude determination system in the non-inertial frame on the moving base.

Application of Improved Fast Dynamic Allan Variance for the Characterization of MEMS Gyroscope on UAV

Microelectromechanical systems (MEMS) are core components in unmanned aerial vehicles (UAV). The precision of MEMS sensors is very important when the GPS signal is invalid. However, the precision and performance of MEMS sensors will be degraded by the changing of environment. Therefore, estimation and identification of the various noise terms existing in MEMS sensors are deemed to be necessary. The Allan variance is a common and standard method to analyze MEMS sensors, but it cannot be used to analyze the dynamic characteristics. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool that could represent the nonstationary behavior of the MEMS signal. As the DAVAR needs to estimate the Allan variance at each time epoch, the computation time grows significantly with the length of the signal series. In this paper, in the case of MEMS gyroscope on UAV, an improved fast DAVAR algorithm based on the choice of relevant time is proposed to shorten the computation time. As an experimental validation, numerical experiments are conducted under the proposed method. The results demonstrate that the improved method could greatly increase the computation speed and does not affect the accuracy of estimation.

Robust output regulation of a triaxial MEMS gyroscope via nonlinear active disturbance rejection

SummaryThis paper presents a nonlinear disturbance rejection–based controller for the robust output regulation of a triaxial microelectromechanical system (MEMS) vibratory gyroscope. In a MEMS gyroscope, parameter variations, mechanical couplings, suspension system nonlinearities, thermal noise, and centripetal/Coriolis forces are the main uncertainty sources. In the dynamical equations of the gyroscope, these uncertainties appear as a matched total disturbance, which does not coincide with the required structure of a standard output regulation problem. More specifically, the total disturbance is not guaranteed to belong to the solution space of a fixed dynamical system. Therefore, we propose a control system that comprises a nominal output regulator equipped with a disturbance rejection loop. On the basis of a suitable reference dynamics of the gyroscope, the control system is developed as the stabilization of a zero‐error invariant manifold in the tracking error space. In the disturbance rejection loop, a nonlinear extended state observer (ESO) is designed to estimate the total disturbance. The convergence of the ESO is analyzed in a Lyapunov‐Lurie framework by linear matrix inequalities (LMIs). In the nominal output regulation loop, the stabilization problem of the desired manifold is tackled by introducing a suitable distance coordinate. Next, to achieve guaranteed attenuation of the ESO estimation errors, an energy‐to‐peak design is pursued. On the basis of the center manifold theory, the stability of the overall closed‐loop system is guaranteed. The efficacy of the proposed control method is assessed through software simulations.

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

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.

Temperature‐dependence improvement for a MEMS gyroscope using triangular‐electrode based capacitive detection method

This work presents analysis and test results on temperature-dependence improvement for a microelectromechanical systems (MEMS) gyroscope based on triangular-electrode based (TEB) capacitive detection method. To reduce the effects of temperature variations on MEMS gyroscopes, TEB capacitive detection method is applied because the extracted amplitude and phase are robust to system parameter fluctuations. In the first place, analytical results for the scale factors and zero-rate outputs, respectively, utilising linear electromechanical amplitude modulation (linear-EAM) method and TEB method are derived. Then experimental results of the temperature characteristics for gyroscopes are conducted. The temperature coefficient of scale factor over the temperature range of −10 to 60°C is reduced from −8845 ppm/°C for linear-EAM method to 1660 ppm/°C for TEB method with an improvement factor of 5.3. Moreover, the temperature-induced zero-rate output variation is decreased from −68.05°/s for linear-EAM method to −29.09°/s for TEB method with an improvement factor of 2.3. Experimental results of temperature-dependence improvement agree well with the theoretical analysis. In the end, Allan variance analysis demonstrates a bias instability of 2.85°/h, and an ARW (angle random walk) of 0.16°/√h with a vacuum-packaged gyroscope using TEB method, which is significantly better than the bias instability 5.47°/h and ARW 0.22°/√h tested using linear-EAM method.

A rapid seismic data calibration technique using integrated micro-electro-mechanical system inertial sensor groups for a 3C vertical seismic profile

Calibration of 3C vertical seismic profile (VSP) data is an exciting challenge because the orientation of the tool is random when only seismic data are considered. We have augmented the sensor package on the VSP tool with micro-electro-mechanical system (MEMS) inertial sensors and applied a gesture measuring method to determine the tool orientation and calibration. This technique can quickly produce high precision, orientation, and angle information when integrated with the seismometer. The augmented sensor package consists of a low-cost triaxial MEMS gyroscope, an electronic compass, and an accelerometer. The technique to process the gesture information is based on the OpenGL software for 3D modeling. We have tested this approach on a large number of field data sets and it appeared to be faster and more reliable than other approaches.

Modeling and Compensation of Random Drift of MEMS Gyroscopes Based on Least Squares Support Vector Machine Optimized by Chaotic Particle Swarm Optimization

MEMS (Micro Electro Mechanical System) gyroscopes have been widely applied to various fields, but MEMS gyroscope random drift has nonlinear and non-stationary characteristics. It has attracted much attention to model and compensate the random drift because it can improve the precision of inertial devices. This paper has proposed to use wavelet filtering to reduce noise in the original data of MEMS gyroscopes, then reconstruct the random drift data with PSR (phase space reconstruction), and establish the model for the reconstructed data by LSSVM (least squares support vector machine), of which the parameters were optimized using CPSO (chaotic particle swarm optimization). Comparing the effect of modeling the MEMS gyroscope random drift with BP-ANN (back propagation artificial neural network) and the proposed method, the results showed that the latter had a better prediction accuracy. Using the compensation of three groups of MEMS gyroscope random drift data, the standard deviation of three groups of experimental data dropped from 0.00354, 0.00412, and 0.00328 to 0.00065, 0.00072 and 0.00061, respectively, which demonstrated that the proposed method can reduce the influence of MEMS gyroscope random drift and verified the effectiveness of this method for modeling MEMS gyroscope random drift.

Offline Calibration for MEMS Gyroscope G-sensitivity Error Coefficients Based on the Newton Iteration and Least Square Methods

With the improvement of the bias instability of Micro-Electromechanical Systems (MEMS) gyroscopes, the g-sensitivity error is gradually becoming one of the more important factors that affects the dynamic accuracy of a MEMS gyroscope. Hence there is a need for correcting the g-sensitivity error. However, the traditional calibration of g-sensitivity error uses a centrifuge. The calibration conditions are harsh, the process is complex and the cost is relatively high. In this paper, a fast and simple method of g-sensitivity error calibration for MEMS gyroscopes is proposed. With respect to the bias and random noise of a MEMS gyroscope, the g-sensitivity error magnitude is relatively small and it is simultaneously coupled with the Earth's rotation rate. Therefore, in order to correct the g-sensitivity error, this work models the calibration for g-sensitivity error coefficients, designs an (8+N)-position calibration scheme, and then proposes a fitting method for g-sensitivity error coefficients based on the Newton iteration and least squares methods. Multi-group calibration experiments designed on a MEMS Inertial Measurement Unit (MEMS IMU) product demonstrate that the proposed method can calibrate g-sensitivity error coefficients and correct the g-sensitivity error effectively and simply.

A novel method of calibrating a MEMS inertial reference unit on a turntable under limited working conditions

Micro-electro-mechanical systems (MEMS) inertial measurement devices tend to be widely used in inertial navigation systems and have quickly emerged on the market due to their characteristics of low cost, high reliability and small size. Calibration is the most effective way to remove the deterministic error of an inertial reference unit (IRU), which in this paper consists of three orthogonally mounted MEMS gyros. However, common testing methods in the lab cannot predict the corresponding errors precisely when the turntable’s working condition is restricted. In this paper, the turntable can only provide a relatively small rotation angle. Moreover, the errors must be compensated exactly because of the great effect caused by the high angular velocity of the craft. To deal with this question, a new method is proposed to evaluate the MEMS IRU’s performance. In the calibration procedure, a one-axis table that can rotate a limited angle in the form of a sine function is utilized to provide the MEMS IRU’s angular velocity. A new algorithm based on Fourier series is designed to calculate the misalignment and scale factor errors. The proposed method is tested in a set of experiments, and the calibration results are compared to a traditional calibration method performed under normal working conditions to verify their correctness. In addition, a verification test in the given rotation speed is implemented for further demonstration.

Design and FEM simulation for a novel resonant silicon MEMS gyroscope with temperature compensation function

A kind of resonant silicon micro-electro-mechanical systems (MEMS) gyroscope with self-temperature compensation function is designed to overcome the problem of conventional MEMS gyroscope, whose measuring precision is greatly affected by the temperature effect. Sensitive element of the system is composed of four symmetrically distributed double ended tuning fork (DETFs). They are of the same dimensions. Two of the DETFs which are closing to the proof mass are used to sense the force effect and temperature effect while the other two DETFs are just used to sense the temperature effect. By comparing these two different conditions, the self-temperature compensation model can be deduced. In order to verify the feasibility of the design, finite element method (FEM) is used to compute the performance of system. It is concluded that in the range of −20 to 80 °C, the maximum relative error of the resonant frequency variation is reduced from 16.3 to 3.1%. Simulating result indicates this scheme of design is effective to overcome the temperature effect of this kind of gyroscope.

Design on PCIe Real-time Measurement and Control Platform for MEMS Gyroscope

This paper introduces a PCIe (PCI Express) real-time measurement and control platform for MEMS (Micro-Electro-Mechanical System) gyroscopes. Through optimization of the PCIe and FPGA (Field Programmable Gate Array) drivers as well as the delay link, the platform realized the closed-loop control of gyroscope in both the driving frequency and amplitude. Consequently, the linear vibration gyroscope could work at the resonant frequency and the amplitude was stable. Considering the real-time performance of the platform and stability of data transmission, analysis from the aspects of software and hardware are presented here. For the PCIe bus transmission, the hardware of FPGA was optimized. The readout time of single data was reduced to 1.8 μs by accelerating controls of bus transmission and PCIe IP core interface. For the system software, the underlying driver and algorithm were streamlined so that the data transmission delay between kernel layer and user layer was decreased. The development of highly-efficient timing control proposal ensured stabilization in data transmission. The proposed platform could reach a 100 kHz sampling and processing rate in PC system, which is enough for the current requirements. Furthermore, the proposed high-rate real-time platform can also be used in more real-time high-demanding systems.

Kurtosis-based IMM filter for multiple MEMS gyroscopes fusion

PurposeThe purpose of this study is to explore a signal processing method to improve the angular rate accuracy of micro-electro-mechanical system (MEMS) gyroscope by combining numerous gyroscopes.Design/methodology/approachTo improve the dynamic performance of the signal processing method, the interacting multiple model (IMM) can be applied to the fusion of gyroscope array. However, the standard IMM has constant Markov parameter, which may reduce the model switching speed. To overcome this problem, an adaptive IMM filter is developed based on the kurtosis of the gyroscope output, in which the transition probabilities are adjusted online by utilizing the dynamic information of the rate signal.FindingsThe experimental results indicate that the precision of the gyroscope array composed of six gyroscopes increases significantly and the kurtosis-based adaptive Markov parameter IMM filter (K-IMM) performs better than the baseline methods, especially under dynamic conditions. These experiments prove the validity of the proposed fusion method.Practical implicationsThe proposed method can improve the accuracy of MEMS gyroscopes without breakthrough on hardware, which is necessary to extend their utility while not restricting the overwhelming advantages.Original/valueA K-IMM algorithm is proposed in this paper, which is used to improve the angular rate accuracy of MEMS gyroscope by combining numerous gyroscopes.

Stability of Ring-Type MEMS Gyroscopes Subjected to Stochastic Angular Speed Fluctuation

Effect of stochastic fluctuations in angular velocity on the stability of two degrees-of-freedom ring-type microelectromechanical systems (MEMS) gyroscopes is investigated. The governing stochastic differential equations (SDEs) are discretized using the higher-order Milstein scheme in order to numerically predict the system response assuming the fluctuations to be white noise. Simulations via Euler scheme as well as a measure of largest Lyapunov exponents (LLEs) are employed for validation purposes due to lack of similar analytical or experimental data. The response of the gyroscope under different noise fluctuation magnitudes has been computed to ascertain the stability behavior of the system. External noise that affect the gyroscope dynamic behavior typically results from environment factors and the nature of the system operation can be exerted on the system at any frequency range depending on the source. Hence, a parametric study is performed to assess the noise intensity stability threshold for a number of damping ratio values. The stability investigation predicts the form of threshold fluctuation intensity dependence on damping ratio. Under typical gyroscope operating conditions, nominal input angular velocity magnitude and mass mismatch appear to have minimal influence on system stability.

Measurement and analysis of certain flight parameters based on MEMS sensors

Abstract. Gyroscopes established one of the fundamental references for attitude and heading in aerospace applications. The information about angular velocities gives input not only for autopilot, but also damping devices, such as yaw or pitch dampers for example. The MEMS (micro-electro-mechanical system) gyroscopes are much less reliable than their laser or fibre-optic cousins. Nevertheless, the availability and low price of MEMS components make this a growing area of application in avionics for general aviation aeroplanes. This paper presents certain results of flight data analysis registered during the flight testing campaign of the new experimental low-power single-engine turbo-propeller utility aeroplane I-31T. The research was focused on identification of oscillation modes, distinctive for the new aeroplane, such as engine precession or shimmy. The data came from a three-axis MEMS gyroscope and accelerometer recorder, placed near to the centre of gravity. Wavelet transform, which was used for analysis, gave better precision in time domain than Fourier transform, especially for signals of low frequency.

A Novel MEMS Gyro North Finder Design Based on the Rotation Modulation Technique.

Gyro north finders have been widely used in maneuvering weapon orientation, oil drilling and other areas. This paper proposes a novel Micro-Electro-Mechanical System (MEMS) gyroscope north finder based on the rotation modulation (RM) technique. Two rotation modulation modes (static and dynamic modulation) are applied. Compared to the traditional gyro north finders, only one single MEMS gyroscope and one MEMS accelerometer are needed, reducing the total cost since high-precision gyroscopes and accelerometers are the most expensive components in gyro north finders. To reduce the volume and enhance the reliability, wireless power and wireless data transmission technique are introduced into the rotation modulation system for the first time. To enhance the system robustness, the robust least square method (RLSM) and robust Kalman filter (RKF) are applied in the static and dynamic north finding methods, respectively. Experimental characterization resulted in a static accuracy of 0.66° and a dynamic repeatability accuracy of 1°, respectively, confirming the excellent potential of the novel north finding system. The proposed single gyro and single accelerometer north finding scheme is universal, and can be an important reference to both scientific research and industrial applications.

Backstepping-Based Recurrent Type-2 Fuzzy Sliding Mode Control for MIMO Systems (MEMS Triaxial Gyroscope Case Study)

This paper presents a novel type-2 fuzzy sliding mode control with nonlinear consequent part in fuzzy rules for control of Micro-Electro-Mechanical Systems (MEMS) gyroscope. The MEMS gyroscope consists of the basic mechanical structure, an electronic transducer to excite the system as well as an electronic sensor to detect the change in the mechanical structures modal shape. A nonlinear consequent part recurrent type-2 fuzzy system is used to approximate the conventional sliding mode control (SMC) law. A supervisory compensator is introduced to eliminate the effect of the approximation error. The adaptive adjustment algorithms for type-2 fuzzy parameters are derived in the sense of projection algorithm and Lyapunov stability theorem. The proposed type-2 fuzzy system has simple structure with six layers. Recurrent feedbacks at the fifth layer uses delayed outputs for improve the performance of type-2 fuzzy system. Finally the proposed type-2 fuzzy sliding mode control system is used to tracking control design with regard to uncertainty in MEMS gyroscope system. Combination of backstepping method and sliding mode control helps to compensate the control signal and get a better performance. The backstepping method is used to improve the global ultimate asymptotic stability and applying the sliding mode control to obtain high response and invariability to uncertainties. Simulation results show the proposed type-2 fuzzy system has better performance than ANFIS-based sliding mode control.

MEMS and FOG Technologies for Tactical and Navigation Grade Inertial Sensors-Recent Improvements and Comparison.

In the following paper, we present an industry perspective of inertial sensors for navigation purposes driven by applications and customer needs. Microelectromechanical system (MEMS) inertial sensors have revolutionized consumer, automotive, and industrial applications and they have started to fulfill the high end tactical grade performance requirements of hybrid navigation systems on a series production scale. The Fiber Optic Gyroscope (FOG) technology, on the other hand, is further pushed into the near navigation grade performance region and beyond. Each technology has its special pros and cons making it more or less suitable for specific applications. In our overview paper, we present latest improvements at NG LITEF in tactical and navigation grade MEMS accelerometers, MEMS gyroscopes, and Fiber Optic Gyroscopes, based on our long-term experience in the field. We demonstrate how accelerometer performance has improved by switching from wet etching to deep reactive ion etching (DRIE) technology. For MEMS gyroscopes, we show that better than 1°/h series production devices are within reach, and for FOGs we present how limitations in noise performance were overcome by signal processing. The paper also intends a comparison of the different technologies, emphasizing suitability for different navigation applications, thus providing guidance to system engineers.

Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

Adaptive neural nonsingular terminal sliding mode control for MEMS gyroscope based on dynamic surface controller

A novel adaptive dynamic surface control (DSC) method for the micro-electromechanical systems gyroscope, which combined the approaches of a radial basis function neural networks (RBFNN) and a nonsingular terminal sliding mode (NTSM) controller was proposed in this paper. In the DSC, a first-order filter was introduced to the conventional adaptive backstepping technique, which not only maintains the advantage of original backstepping technique, but also reduces the number of parameters and avoids the problem of parameters expansion. The RBFNN is an approximation to the gyroscope’s dynamic characteristics and external disturbances. By introducing a nonsingular terminal sliding mode controller which ensuring the control system could reach the sliding surface and converge to equilibrium point in a finite period of time from any initial state. Finally, simulation results prove that the proposed approach could reduce the chattering of inputs, improve the timeliness and effectiveness of tracking in the presence of model uncertainties and external disturbances, demonstrating the excellent performance compared to nonsingular terminal sliding mode control (NTSMC).

Root Cause Analysis of Zero-Rate Output Sources in an MEMS Gyroscope

This paper analyzes the root causes of zero-rate output (ZRO) in microelectromechanical system (MEMS) vibratory gyroscopes. ZRO is one of the major challenges for high-performance gyroscopes. The knowledge of its causes is important to minimize ZRO and achieve a robust sensor design. In this paper, a new method to describe an MEMS gyroscope with a parametric state space model is introduced. The model is used to theoretically describe the behavioral influences. A new, more detailed and general gyroscope approximation is used to vary influence parameters, and to verify the method with simulations. The focus is on varying stiffness terms and an extension of the model to other gyroscope approximations is also discussed.