Gyro Error Research Articles

Event-triggered finite-time adaptive neural network control for quadrotor UAV with input saturation and tracking error constraints

In this article, an event-triggered finite-time adaptive neural network control tracking strategy is proposed for quadrotor unmanned aerial vehicle (UAV) with input saturation and error constraints. Firstly, the radial basis function neural networks (RBFNNs) are adopted to identify the unknown uncertainty of quadrotor UAV model from the installation errors, gyroscope errors and so on. An auxiliary equation is constructed to deal with input physical saturation from the actuator motors. Additionally, by combining the performance function and error transformation, the issue of error constraint is solved. Based on the Lyapunov stability theory and event-triggered mechanisms, a finite-time adaptive neural network scheme is developed to ensure that the closed-loop quadrotor UAV system is semi-globally practically finite-time stable, and save the computation, resources, and transmission load. Finally, the simulation results illustrate the good tracking performance of quadrotor UAV by using the proposed control strategy.

Analysis of the Temperature Field Characteristics and Thermal-Induced Errors of Miniature Interferometric Fiber Optic Gyroscopes in a Vacuum Environment

This paper investigates the mechanism of thermal-induced errors in interferometric fiber optic gyroscopes (IFOGs) caused by temperature changes in a vacuum environment, proposing a method for calculating thermal-induced errors in small fiber coils. Firstly, based on the Shupe effect and the thermal stress caused by temperature changes around the fiber coil, a three-dimensional thermal-induced error model for small fiber coils is established. Secondly, a spatial fiber optic inertial measurement unit (IMU) model is designed using the Creo 3D modeling software (creo 7.0.0). The model is then imported into the Ansys finite element simulation software (ANSYS Workbench 15.0), where a temperature field is applied to the IMU based on actual temperature profiles to obtain the temperature distribution of the fiber coil at different times in a vacuum state. These data are then used in the three-dimensional thermal-induced error model to calculate the thermal-induced error of the FOG. Finally, a thermal vacuum experimental platform is set up to collect temperature variation data from the inertial measurement components. The experimental data are compared with the three-dimensional error model proposed in this paper as well as traditional error models. The root mean square error is approximately 33% lower than that of traditional error calculation methods, which also proves the theoretical accuracy.

Stochastic analysis of drift error of gyroscope in the single-axis attitude determination

Understanding and mitigating the various stochastic errors in gyroscope measurements is crucial for accurate attitude determination. White noise and bias instability can introduce drift errors, reducing the system’s accuracy. Efficient sensor selection and algorithm design necessitate a thorough understanding of these influences and how they propagate throughout the system. This paper addresses the propagation of significant stochastic errors in the attitude determination system, including white noise (angle random walk), bias instability, rate random walk, and correlated noise. The paper discusses the modeling strategy and statistical characteristics of these error contributors. It then evaluates the variance propagation of these errors within the output of a single-axis attitude determination system. The presented analysis calculates and compares the impact of each source of error on the system’s precision over time. Experiments with the MPU6050 and L3G4200D sensors are conducted to validate the analytical results.

An Improved Initial Alignment Method Based on SE2(3)/EKF for SINS/GNSS Integrated Navigation System with Large Misalignment Angles.

This paper proposes an improved initial alignment method for a strap-down inertial navigation system/global navigation satellite system (SINS/GNSS) integrated navigation system with large misalignment angles. Its methodology is based on the three-dimensional special Euclidean group and extended Kalman filter (SE2(3)/EKF) and aims to overcome the challenges of achieving fast alignment under large misalignment angles using traditional methods. To accurately characterize the state errors of attitude, velocity, and position, these elements are constructed as elements of a Lie group. The nonlinear error on the Lie group can then be well quantified. Additionally, a group vector mixed error model is developed, taking into account the zero bias errors of gyroscopes and accelerometers. Using this new error definition, a GNSS-assisted SINS dynamic initial alignment algorithm is derived, which is based on the invariance of velocity and position measurements. Simulation experiments demonstrate that the alignment method based on SE2(3)/EKF can achieve a higher accuracy in various scenarios with large misalignment angles, while the attitude error can be rapidly reduced to a lower level.

MWD Gyroscope Error Compensation Based on Equivalent Reverse Rotation

MWD Gyroscope Error Compensation Based on Equivalent Reverse Rotation

Identification Method for Assembly Pose Errors of Flat Electrode Hemispherical Resonator Gyro

Identification Method for Assembly Pose Errors of Flat Electrode Hemispherical Resonator Gyro

Separation of mass and gap errors of hemispherical resonator gyroscopes by varying bias voltage

For hemispherical resonator gyroscopes (HRGs), mass imperfections and capacitive gap nonuniformity jointly influence the frequency mismatch and degrade the gyroscope performance. However, the coupling mechanism and separation of these two errors are rarely discussed. This paper proposes, for the first time, a novel method of separating mass imperfections and gap nonuniformity of HRGs, based on a dynamics model considering both the two errors. By measuring the frequency mismatches and principal axes of stiffness at different bias voltages, the mass imperfections and gap nonuniformity can be separately obtained. The method is investigated in detail by simulation, and validated by experiment on three different HRGs. The experimental results agree well with the theoretical analysis, demonstrating the effectiveness of the model and the separation method. Our method may contribute to high-precision HRG manufacture, and can be conveniently applied to other Coriolis vibrating gyroscopes (CVGs) with electrostatic actuation.

A Stepwise Calibration Method for Successive Start-Up Errors of the Three-Axis Gyroscope Based on the Characteristics of Compass Heading Alignment Error

A Stepwise Calibration Method for Successive Start-Up Errors of the Three-Axis Gyroscope Based on the Characteristics of Compass Heading Alignment Error

Autonomous method for a strapdown inertial navigation system calibration in operation in operation

Strapdown inertial navigation systems (SINS) are widely used in modern air transport. The service life of such systems is decades. During this time, the characteristics of such systems may deteriorate due to the degradation of inertial sensors - gyroscopes and accelerometers. Under these conditions, in order to maintain the required accuracy of the SINS during the entire period of operation, it is necessary either to periodically carry out routine maintenance with the onboard system, or to continuously adapt the used sensor measurement model in terms of compensating for errors that arise. The second direction, which we will call calibration, has the advantage over the first one that it is carried out automatically by the system itself and does not require any additional equipment or additional maintenance work. The known method of SINS recalibration is based on the integration of information from the SINS and from the receiver of satellite radio navigation signals (SRNS). Such calibration, firstly, significantly depends on the availability and quality of satellite information, and secondly, it is possible only for integrated navigation systems in which the inertial subsystem is supplemented by a SRNS receiver. In contrast to the known method, this article solves the problem of autonomous SINS calibration, which is carried out after each flight. The solution is based on a linearized inertial navigation error model based on the boundary conditions of the state vector (at the beginning and end of the flight). The external information used consists only of the initial values of the coordinates and the current measurements of the baroaltimeter. As a result of the decision at the end of the flight, the errors of gyroscopes and accelerometers are determined, as well as the error in determining the final values of latitude and longitude in the SINS. Sensor errors can be used in subsequent system activations, which improves the accuracy of its operation as a whole. The analysis of the suitability and effectiveness of the developed methodology was carried out on a typical flight simulation program.

A high-precision online compensation method for random errors of optical gyroscope

The traditional Allan variance cannot reflect the time-varying characteristics of random error signals, and the dynamic Allan variance cannot simultaneously guarantee both the signal dynamic tracking performance and confidence of variance estimation due to adopting the sliding window with fixed window length to intercept and segment random error signals. To address these issues, a dynamic Allan variance analysis method with adaptive window length is proposed. Based on the idea of piecewise stability of time-varying random error signals, a sliding window is introduced to intercept and segment the signal to be analyzed along the time axis, and the Allan variance analysis results of all signal segments are synthesized to track and describe the time-varying characteristics of the signal. Then according to the changes in the statistical characteristics of the random error signal, an adaptive factor is constructed to adaptively adjust the length of the sliding window, thereby guaranteeing both the signal dynamic tracking performance and confidence of variance estimation at the same time. On this basis, this method is applied to the online compensation of optical gyroscope random errors, and then a high-precision online compensation method for random errors of optical gyroscope is proposed. The experimental results show that the proposed method can achieve high-precision online compensation for the time-varying random error signals of optical gyroscope measured in complex environment such as uncertainty and noise interference.

Design and Experiment of MEMS Solid-State Wave Gyroscope Quadrature Error Correction System

A novel gyroscope quadrature error correction system based on quadrature force correction is introduced in this paper. The source of quadrature error of MEMS solid-state wave gyroscope is analyzed. The main source of quadrature error is the inevitable machining error. The gyroscope system model is established, the quadrature error correction method is proposed, and the quadrature error correction system is simulated. Through the comparative test, the gyroscope with quadrature error correction system has better performance. With the addition of quadrature error correction system, the scale factor of the gyroscope changes from 1.13 mV/°/s to 1.02 mV/°/s, the nonlinearity is increased from 1382.7ppm to 795.4 ppm, and the asymmetry is improved from 1532.4ppm to 945.1ppm, the angle random walk (ARW) from 269.1 °/h/√Hz to 39.45 °/h/√Hz, and the bias stability from 46.62 °/h to 6.785 °/h.

Systematic Measurement of Temperature Errors of Positive and Negative FOG Scale Factors Using a Low-Precision Turntable

Measurement of temperature errors of fiber optic gyro (FOG) scale factor is important in FOG technology. In traditional methods, the measurement errors of FOG scale factors are greatly affected by the turntable’s orientation control errors. This article proposes a systematic method to measure the positive and negative FOG scale factor errors using a low-precision turntable. The relationship between the inertial navigation errors and the complete inertial measurement unit errors is revealed. A simplified tracking algorithm is devised to obtain the change rates of the velocity errors with lower computation. A measurement procedure is designed, with three groups of π and -π rotations around the east axis of the turntable at each temperature. Observation equations are derived to estimate the positive and negative FOG scale factor errors. Simulation and experimental results show that a low-precision turntable can accurately measure the FOG scale factor errors at each temperature. Furthermore, temperature errors of accelerometer biases, scale factors, and nonlinear scale factors can also be measured at the same time using the rotation sequences and formulas in this article without additional rotations.

MEMS-IMU automatic calibration system design and implementation

Aiming at the problems of traditional calibration, long calibration cycles, and low efficiency of traditional error calibration methods for MEMS inertial devices, a MEMS IMU automatic calibration system is proposed. Firstly, the error mechanism of MEMS-IMU is analyzed, the error model is established, and the calibration scheme is designed. Then, the automatic control of the turntable and the automatic data acquisition of MEMS inertial devices are realized by designing the data interaction mechanism between the system equipment. Finally, the least square method is used to identify the model parameters. The experimental results show that this method can meet the requirements of multi-position and multi-rate calibration. After compensation, the relative errors of the MEMS gyroscope and accelerometer are 0.04% and 0.15%, respectively, and the cross-coupling error of the MEMS gyroscope is reduced to about 0.1 °/s. At the same time, the whole calibration process is easy to operate, which greatly shortens the calibration time and improves the calibration efficiency.

Research on A Gyro Error Calibration Method Based on Dynamic Compensation

Gyroscopes in Micro-Electro-Mechanical Systems (MEMS) technology have high accuracy, convenient use, and broad application prospects. In practical applications, it is found that angular rate error is one of the main reasons that affect the output accuracy of gyroscopes. In the angular rate error calibration of MEMS gyroscopes, the method of calibrating the gyroscopes only by changing the bias and scale coefficients obtained by fitting cannot meet the angular rate error calibration of MEMS gyroscopes whose dynamic range exceeds . Therefore, the research proposes an improved calibration method to solve the problem of angular rate error, using dynamic compensation algorithms to achieve dynamic compensation for the angular rate of MEMS gyroscopes. Experiments show that using the dynamic compensation calibration method proposed in this paper, the root mean square error of the angular rate of MEMS gyroscopes has decreased by 52.37% compared to the previous one, verifying the feasibility of this method.

MIMU Optimal Redundant Structure and Signal Fusion Algorithm Based on a Non-Orthogonal MEMS Inertial Sensor Array.

A micro-inertial measurement unit (MIMU) is usually used to sense the angular rate and acceleration of the flight carrier. In this study, multiple MEMS gyroscopes were used to form a spatial non-orthogonal array to construct a redundant MIMU system, and an optimal Kalman filter (KF) algorithm was established by a steady-state KF gain to combine array signals to improve the MIMU's accuracy. The noise correlation was used to optimize the geometric layout of the non-orthogonal array and reveal the mechanisms of influence of correlation and geometric layout on MIMU's performance improvement. Additionally, two different conical configuration structures of a non-orthogonal array for 4,5,6,8-gyro were designed and analyzed. Finally, a redundant 4-MIMU system was designed to verify the proposed structure and KF algorithm. The results demonstrate that the input signal rate can be accurately estimated and that the gyro's error can also be effectively reduced through fusion of non-orthogonal array. The results for the 4-MIMU system illustrate that the gyro's ARW and RRW noise can be decreased by factors of about 3.5 and 2.5, respectively. In particular, the estimated errors (1σ) on the axes of Xb, Yb and Zb were 4.9, 4.6 and 2.9 times lower than that of the single gyroscope.

Digital Control and Demodulation Algorithm for Compact Open-Loop Fiber-Optic Gyroscope.

With the advantages of small size, low cost, and moderate accuracy, an open-loop fiber-optic gyroscope (FOG) has a wide range of applications around control and automation. For the most cost-sensitive applications, a simple and stable digital algorithm with a reduced control-circuit volume and cost is highly desirable to realize high-precision control of a FOG. In this work, a new algorithm for an open-loop FOG is proposed based on the discrete multi-point demodulation in the sinusoidal modulation period. Utilizing this algorithm, stable control and angular velocity calculation of a gyro are realized with effectively suppressed gyro error. The use of this algorithm greatly reduces the requirements for processing power and simplifies the gyro circuit. Based on this algorithm, a digital FOG with a volume of only 25 × 20 × 40 mm3 achieves a bias instability of less than 0.15°/h, an angle random walk (ARW) of less than 0.015°/√h, a start-up time of less than 1 s, and a 3 dB bandwidth beyond 160 Hz. This low-cost, compact, and high-performance gyro is sufficient to satisfy the requirements of applications in the navigation and control fields such as unmanned driving.

An optimal calibration method for gyro and star sensor based on observability analysis

The major challenge of current strapdown inertial navigation system/celestial navigation system (SINS/RCNS) is failing to calibrate all the error coefficients of gyro and star sensor in-flight accurately, which will lead to the attitude accuracy degradation. To address this question, this paper proposes an optimal calibration method based on observability analysis. Here, we derive the star sensor measurement model with respect to initial alignment errors, gyro errors, and star sensor installation errors. And the observability analysis is employed to explain the reason why all the error coefficients can be estimated effectively by three maneuvers merely. Finally, the optimal observation sequence is determined based on the fisher information matrix (FIM). The proposed optimal calibration method is evaluated by a representative suborbital flight vehicle trajectory, which represents significant improvements in estimation accuracy of error coefficients, and realizes the attitude accuracy enhancements.

Research on automatic early warning of UAV attitude abnormal state based on MEMS sensor

The Unmanned Aerial Vehicle's (UAV) attitude control is crucial to the success of the mission. On the basis of this, the paper suggests a paradigm for autonomous early warning of improper UAV attitude based on MEMS sensors. To obtain early warning of anomalous UAV attitude, the model solves UAV attitude using the quaternion approach and employs a fading Kalman filter to correct for MEMS gyroscope inaccuracy. The simulation test demonstrates that in the static state, the errors of the drone's pitch angle and roll angle are within 0.2°, and the heading angle error is about 0.5°. In the high manoeuvring state, the errors of the UAV's pitch angle and roll angle are all within 0.5°, and the mean value of the heading angle error is also controlled within 2°. The experiment achieves high-precision automated warning of aberrant attitude by filtering the fading Kalman filter to correct the random error of the UAV gyroscope. It also increases the precision with which human motion is measured. The suggested approach promotes the growth of the UAV sector.

Modeling, identification and compensation for assembly error of whole-angle mode hemispherical resonator gyro

The hemispherical resonator and the electrode base are prone to tilt and eccentricity during the assembly process, which greatly restricts the working accuracy of gyro. In order to reduce this impact, the influence of the resonator assembly error on gyro drift under different electrode configuration schemes is analyzed. Secondly, an error parameters identification method based on nonlinear optimization is proposed, which can realize the synchronous identification of the two channels' gain ratio and misalignment angle. Finally, a signal demodulation compensation scheme is designed to compensate the error parameters. The experimental results show that after the feedforward compensation, the angular rate oscillation amplitude under dynamic conditions is reduced by two orders of magnitude, and the bias stability of gyro output is improved by 5 times.

Research on Identification and Suppression of Vibration Error for MEMS Inertial Sensor in Near-Bit Inclinometer

The measurement information of the traditional conventional measurement while drilling (MWD) method lags seriously because the installation position is far from the bit. However, the near-bit inclinometer will generate a large number of vibration interference signals when the bit breaks the rock in the drilling process, resulting in the continuous increase in errors measured by the microelectromechanical system (MEMS) inertial sensor. Aiming at the problems of low accuracy and poor stability of near-bit inclinometer under the interference of long-term complex vibration signals, a vibration error identification and suppression method of MEMS inertial sensor of near-bit inclinometer is proposed in this article. Firstly, the characteristics of the vibration signal of near-bit inclinometer are analyzed. The near-bit vibration errors of first-order linear vibration and high-order nonlinear vibration are identified, and the vibration characteristics are analyzed, the error model of gyroscope and accelerometer under complex vibration interference is established, and then the vibration error suppression model of inclinometer gyroscope and accelerometer is established based on the hybrid Kalman filter (KF) and unscented KF (UKF) algorithm. Finally, the hardware and software experimental platform of near-bit inclinometer is built. The experimental results show that the dynamic measurement errors of inclination, toolface, and azimuth are kept within ±0.6°, and the vibration errors of gyroscope and accelerometer are effectively suppressed.