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This research proposes a new fractional robust data-driven control method to control a nonlinear dynamic micro-electromechanical (MEMS) gyroscope model. The Koopman theory is used to linearize the nonlinear dynamic model of MEMS gyroscope, and the Koopman operator is obtained by using the dynamic mode decomposition (DMD) method. However, external disturbances constantly affect the MEMS gyroscope. To compensate for these perturbations, a fractional sliding mode controller (FOSMC) is applied. The FOSMC has several advantages, including high trajectory tracking performance and robustness. However, one of the drawbacks of FOSMC is generating high control inputs. To overcome this limitation, the researchers proposed a compound controller design that applies fractional proportional integral derivative (FOPID) to reduce the control efforts. The simulation results showed that the proposed compound Koopman-FOSMC and FOPID (Koopman-CFOPIDSMC) outperformed two other controllers, including FOSMC and Koopman-FOSMC, in terms of performance. Therefore, this research proposes an effective approach to control the nonlinear dynamic model of MEMS gyroscope. [ABSTRACT FROM AUTHOR]

A neural adaptive robust control method is proposed for the desired tracking of micro-electro-mechanical system (MEMS) triaxial gyroscope. In this work, input constraints and external disturbance are taken into account, and a barrier Lyapunov function (BLF) is used to ensure that the constraints are not violated and that tracking performance is achieved. In the presented control approach, RBFNNs with a non-zero parameter are employed to approximate the lumped uncertainties of the system, where the approximation precision can be modified online by the provided adaptive laws in the control strategy. All of the signals in the closed-loop system are uniformly finally bounded (UUB) thanks to the designed control mechanism, which may overcome the limitation of the finite universal approximation domain. The effectiveness of the suggested control is demonstrated by the comparison of simulation results. [ABSTRACT FROM AUTHOR]

This article is concerned with the method of calibrating the temperature drift and random drift of Micro-Electro-Mechanical System (MEMS) gyroscope to improve the precision of MEMS gyroscope application. These methods include two steps. In the first step, the optimized BP neural network is used to establish the temperature drift error model of the MEMS gyroscope, and the B-spline method is used to improve the storage and calculation efficiency of the temperature drift calibration. In the second step, since the random drift error of a single sensor is difficult to reduce the data of multiple MEMS gyroscope sensors that have completed temperature drift calibration are fused.The error calibration evaluation indicators all use SSE (The sum of squares due to error) to compare the advantages of the proposed method.In the experimental part,the four most common MEMS chips MPU6050(including a three-axis gyroscope and accelerometer sensor) are used in the market to verify the effect of the proposed method in drift error calibration. Finally, it is proved that the data fusion of a Multi-sensor is not only significantly better than the random drift error of a single sensor. Moreover, with the increase in the number of fusion sensors, the calibration effect has a trend of gradual improvement. [ABSTRACT FROM AUTHOR]

Data-driven control methods are strong tools due to their predictions for controlling the systems with a nonlinear dynamic model. In this paper, the Koopman operator is used to linearize the nonlinear dynamic model. Generating the Koopman operator is the most important part of using the Koopman theory. Dynamic mode decomposition (DMD) is used to obtain eigenfunction for producing the Koopman operator. Then, a fractional order PID (FOPID) controller is applied to control the linearized dynamic model. A swarm intelligence bat optimization algorithm is utilized to tune the FOPID controller's parameters. Simulation results on micro-electromechanical systems (MEMS) gyroscope under conventional PID controller, FOPID, Koopman-based FOPID controller (Koopman-FOPID), and Koopman-FOPID control optimized by bat algorithm (Koopman-BAFOPID) show that the proposed Koopman-BAFOPID controller has better performance in comparison with three other controllers in terms of high tracking performance, low tracking error, and low control efforts. [ABSTRACT FROM AUTHOR]

Angular velocity measurement is a very important measurement parameter in industrial manufacturing field and different scientific applications. The design of gyro measurement and control circuit is always the most challenging and reliable task of angular velocity measurement system. This paper introduces the design and implementation of a measurement and control circuit for digital output of gyro for angular velocity measurement. The design of measuring and controlling circuit with high precision digital output is presented. A method of on-chip scale factor and zero output compensation correction for angular velocity measurement is introduced. Peak detection and proportional integral controller are used to replace the phase-locked loop in the driving circuit, which makes the driving loop of gyro system have good robustness. A sigma-delta (ΣΔ) digital-to-analog converter is designed for digital output of angular velocity signal. Finally, the least square method is used to evaluate the nonlinearity of angular velocity measurement system according to test results, and the zero output and scale factor uncertainty of the measurement system are evaluated. [ABSTRACT FROM AUTHOR]

This paper discusses a perturbation compensation-based robust vibration controller for single-axis MEMS gyroscope applications. The purpose is to obtain a robust and stable operation mode of the gyroscope and improve its capability in estimating time-varying angular velocities. First, based on the force-balancing operation mode, an estimator is designed for real-time identification of input angular velocities. Next, to facilitate the angular velocity sensing, a control system is designed that comprises a nominal controller gathered with a perturbation compensator. In the perturbation compensation stage, a nonlinear extended state observer (NESO) is designed to estimate the perturbations due to parametric uncertainty, undesired couplings, Coriolis acceleration and mechanical-thermal noises. In the nominal control stage, by applying the internal model principle, an output regulator is developed. The outputs of both NESO and nominal regulator are combined to attain the robust vibration control of the gyroscope. The closed-loop stability and robustness are analytically proved through Lyapunov's direct method. To show the effectiveness of the proposed closed-loop operation mode, extensive numerical simulations are carried out by the experimental data of an inertial navigation system (INS). [ABSTRACT FROM AUTHOR]

A mathematical model of torque-to-balance MEMS gyroscope with a drive mode in plane is developed. The model considers compensational control loop, proof-mass dynamics, electromechanical nonlinear effects in capacitive transducers and the inequality of their parameters. The response of the resulting system to translational vibrations is investigated. Qualitative coincidence of simulation results with experimental data is obtained. A way of increasing vibration reliability is highlighted. [ABSTRACT FROM AUTHOR]

In this paper, a dynamic global proportional integral derivative (PID) sliding mode controller based on an adaptive radial basis function (RBF) neural estimator is developed to guarantee the stability and robustness in the presence of a lumped uncertainty for a micro electromechanical systems (MEMS) gyroscope. This approach gives a new dynamic global PID sliding mode manifold, which not only enables system trajectory to run on the global sliding mode surface at the start point more quickly and eliminates the reaching phase of the conventional sliding mode control, but also restrains the steady-state error and reduces the chattering via a dynamic PID sliding surface. A RBF neural network (NN) system is employed to estimate the lumped uncertainty and eliminate the chattering phenomenon at the same time. Additionally, adaptive laws and dynamic global PID sliding control gains that ensure the asymptotic stability of the close-loop system are proposed, together with the techniques for deciding which kind of basis function should be selected. Finally, simulation results demonstrate the effectiveness of RBFNN dynamic global PID sliding mode control method, meanwhile some comparisons are made to verify the good properties of the suggested control approach. [ABSTRACT FROM AUTHOR]

In this paper, a novel adaptive control scheme that incorporates fully tuned radial basis function (RBF) neural network is proposed for the control of MEMS gyroscope with respect to external disturbances and model uncertainties. An adaptive fully tuned RBF neural network controller is used to compensate the effect of external disturbances and model uncertainties, thus improving the dynamic characteristics and robustness of the MEMS gyroscope. The fully tuned RBF neural network compensating controller and the adaptive nominal controller are combined in the unified Lyapunov framework to ensure the stability of the control system. By using the proposed scheme, not only the effect of model uncertainties and external disturbances can be eliminated, but also satisfactory dynamic characteristics and strong robustness can be obtained. Simulation studies are implemented to verify the effectiveness of the proposed scheme and demonstrate that the fully tuned RBF network control has better robustness and dynamic characteristics than traditional RBF network control. [ABSTRACT FROM AUTHOR]

This paper proposes a novel robust design method for the sense mode of a MEMS vibratory gyroscope based on fuzzy reliability and Taguchi design. The principles of fuzzy reliability and Taguchi design are both introduced and described in detail. Experimental results demonstrate that the signal to noise ratio of the robust design scheme is better than those of the other experimental schemes. Over the full temperature range from −40 to 80°C, the temperature sensitivities of phase margin, gain margin, sensitivity margin, the maximum amplitude of open loop system, bandwidth of closed loop system, and the performance function of the robust design system are all smaller than those of the original design system. Meanwhile, the temperature sensitivity of the bandwidth of the robust design system is improved to 126 from 1075 ppm/°C. Moreover, the bias drift over the full temperature range of the robust design system is improved to 61°/h from 179°/h. [ABSTRACT FROM AUTHOR]

In this paper, we study the dynamics, transfer of energy and control of the vibrations of micro-electromechanical system (MEMS) gyroscope with linear and nonlinear parametric excitations. This leads to two-degree-of-freedom system. The coupling of the system equations is responsible for energy transfers of the two vibration modes (drive mode and sense mode) and for the resonance in MEMS gyroscope. The resulting governing equation is in the form of a cubic Mathieu equation coupled to a Duffing equation. The averaging method is applied to obtain the frequency response equations near simultaneous sub-harmonic and internal resonance. The stability of the steady-state solution near the worst resonance case is studied and discussed. The effects of the different parameters on the two modes of system behavior are studied numerically. Poincaré maps are used to determine stability and plot bifurcation diagrams. Comparison between optimal linear feedback control and active control via negative nonlinear cubic velocity feedback in the presence of parameter uncertainties and noise measurement are done. The numerical results of stability, phase planes and time history are achieved using MATLAB and MAPLE programs. [ABSTRACT FROM AUTHOR]

In this paper, a micromachined gyroscope system composed of a vibratory gyroscope with its interface ASIC is presented. The system adopts a DC sensing method to detect the capacitive motion, which is insensitive to the mismatch of the gyroscope capacitors and can eliminate high frequency signals from the chip. Therefore it offers a commendable noise performance with simplified topology. Low noise design can be achieved by a continuous-time charge sensitive amplifier with the input-referred noise voltage of 9.833 nV/rtHz at 10 kHz. A novel high voltage (HV) buffer is adopted in the drive mode to strengthen its drive signal, so that the common-mode voltage of it is made at 5 V that is compatible with the gyroscope. The HV buffer utilizes two sets of power supply to achieve both good noise performance and HV output. The ASIC chip is fabricated in the 0.35 μm 2P4M BCD HV process, and is 2.5×2.0 mm in dimension. The test results prove that the system achieves a stable closed-loop oscillation in the drive mode. Furthermore, the in-phase demodulation result of the gyroscope system achieves a nonlinearity of 0.14% within the sense range of 0°-500°/s. [ABSTRACT FROM AUTHOR]

This paper presents a MEMS gyroscope control system of using a high-order band-pass continuous-time sigma-delta modulator. Compared with a low-pass discrete-time sigma-delta modulator based solution, the band-pass modulator can considerably decrease the sampling frequency; moreover, the continuous-time architecture has an obvious advantage on PCB prototyping and shorter lead time of the implementation in hardware. System level simulations using MATLAB/Simulink show the proposed sixth order sigma-delta modulator can achieve a high SNR of 100 dB for an angular rate input with an amplitude of 200°/s and a frequency of 32 Hz. A PCB circuit implementation is simulated using Orcad/PSpice to analyze the stability, and implemented in hardware. Measurement of the power spectral density of the output bitstream reveals a noise floor of −90 dBV/Hz 1/2. The prototype is tested on a rate table with an angular rate input, verifying that the principle of the approach of using an electro-mechanical band-pass sigma-delta modulator control system for a MEMS gyroscope. [ABSTRACT FROM AUTHOR]

Micro electro-mechanical systems (MEMS) are increasingly being used in measurement and control problems due to their small size, low cost, and low power consumption. The vibrating gyroscope is a MEMS device that will have a significant impact on stability control systems in the transportation industry. This paper investigates the application of a modified model reference adaptive control for MEMS gyroscope. Using this adaptive control algorithm, an estimation of the angular velocity and the damping and stiffness coefficients in real time is easily computable. Changing the conventional model reference input makes it feasible to utilize a low pass filter to remove unwanted oscillations caused by high adaptation gain. This new adaptive control technique enables quick compensation for large changes in the system dynamics, providing consistent estimation of gyroscope parameters including angular velocity and large robustness to parameter variations and external disturbances. The asymptotic stability of the mentioned adaptive controller is guaranteed using the Lyapunov direct method. Numerical simulation is presented to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

Microelectromechanical systems (MEMSs) pose unique measurement and control problems compared with conventional ones because of their small size, low cost, and low power consumption. The vibrating gyroscope is one of those MEMS devices that have significant potential in many industry applications. When the MEMS gyroscope system is considered simultaneously with the coupling terms, the exogenous disturbances and the parameter variations, the controller design of this system becomes very challenging. This paper investigates the primary control problem of a perturbed vibrating MEMS gyroscope. A nonlinear robust adaptive control scheme is proposed for the drive axis of a vibrating MEMS gyroscope. By combining the dynamic surface control (DSC) method with the H-infinity disturbance attenuation technique, a simpler systematic design procedure is developed. The derived H-infinity controller has a simplified structure, and it can drive the drive axis to resonance, regulate the output amplitude of the drive axis to a desired value, and attenuate the generalized disturbances. The features of the derived controller are discussed and illustrated by the simulation of a closed-loop system. The analysis and simulation show that the obtained controller possesses good adaptability and robustness to system uncertainties. [ABSTRACT FROM AUTHOR]

Recently, several micro electro-mechanical systems (MEMS) such as a MEMS gyroscope have been developed by using micro manufacturing technologies. Micro scale products, however, usually have a relatively large manufacturing uncertainty compared to normal macro scale products. It is quite expensive to lower the variance of material properties as well as the geometric properties of a micro scale product. The material and geometric uncertainties caused by a micro manufacturing process inevitably lead to the uncertainty of the product performance. Therefore, to achieve a reliable design of a product, the performance uncertainty of the product, which is often expressed by the variance or the standard deviation, needs to be estimated in a reliable way. In this paper, the equations of motion of a MEMS gyroscope model are derived to analyze the system performance indices (sensitivity and bandwidth). The mean values of the design variables are determined from the requirements of product size, maximum vibration amplitude, and driving frequency. Then the standard deviation of some critical design variables is determined from the performance requirements. Finally, a statistical analysis procedure based on sample statistics is proposed to estimate the confidence interval of the performance index statistics. [ABSTRACT FROM AUTHOR]