This paper presents a novel multi-objective parameter optimization method based on the genetic algorithm (GA) and adaptive moment estimation (Adam) algorithm for the design of a closed-loop control system for the sense mode of a Microelectromechanical systems (MEMS) gyroscope. The proposed method can improve the immunity of the control system to fabrication tolerances and external noise. The design procedure starts by deriving a parameterized model of the closed-loop of the sense mode. The loop parameters are then optimized by the GA. Finally, the ensemble of optimized loop parameters is tested by Monte Carlo analysis to obtain a robust optimal solution. Simultaneously, the Adam-least mean square (LMS) demodulator, which is appropriate for the demodulation of very noisy signals, is also presented. Compared with the traditional method, the time consumption of the design process is reduced significantly. The digital control system is implemented by the print circuit board based on embedded Field Programmable Gate Array (FPGA). The experimental results show that the optimized control loop has achieved a better performance, the system bandwidth in open-loop and optimal closed-loop control system is about 23 Hz and 101 Hz, respectively. Compared to a non-optimized closed-loop system, the bias instability reduced from 0.0015°/s to 7.52 × 10−4°/s, the scale factor increased from 17.7 mV/(°/s) to 23 mV/(°/s) and the non-linearity of the scale factor reduced from 0.008452% to 0.006156%.
This paper presents a novel capacitive microelectromechanical systems (MEMS) accelerometer with slanted supporting beams and all-silicon sandwich structure. Its sensing mechanism is quite similar to an ordinary sandwich-type MEMS accelerometer, except that its proof mass is suspended by a beam parallel to the {111} plane of a (100) silicon wafer. In this way, each sensing element can detect accelerations in two orthogonal directions. Four of these sensing elements could work together and constitute a 3-axis micro-accelerometer by using a simple planar assembly process. This design avoids the traditional 3-axis accelerometer’ disadvantage of possible placement inaccuracy when assembling on three different planes and largely reduces the package volume. The slanted-beam accelerometer’s performance was modeled and analyzed by using both analytical calculations and finite element method (FEM) simulations. A prototype of one sensing element was fabricated and tested. Measured results show that this accelerometer has a good bias stability 76.8 ppm (1σ, tested immediately after power on), two directional sensitivities (sensitivity angle α = 45.4°) and low nonlinearity (<0.5%) over a sensing range up to ±50 g, which demonstrates a great opportunity for future high-precision three-axis inertial measurement.
This paper presents a bias drift self-calibration method for micro-electromechanical systems (MEMS) gyroscopes based on noise-suppressed mode reversal without the modeling of bias drift signal. At first, the bias drift cancellation is accomplished by periodic switching between operation mode of two collinear gyroscopes and subtracting the bias error which is estimated by the rate outputs from a consecutive period interval; then a novel filtering algorithm based on improved complete ensemble empirical mode decomposition (improved complete ensemble empirical mode decomposition with adaptive noise—CEEMDAN) is applied to eliminate the noise in the calibrated signal. A set of intrinsic mode functions (IMFs) is obtained by the decomposition of the calibrated signal using improved CEEMDAN method, and the threshold denoising method is utilized; finally, the de-noised IMFs are reconstructed into the desired signal. To verify the proposed method, the hardware circuit with an embedded field-programmable gate array (FPGA) was implemented and applied in bias drift calibration for the two MEMS gyroscopes manufactured in our laboratory. The experimental results indicate that the proposed method is feasible, and it achieved a better performance than the typical mode reversal. The bias instability of the two gyroscopes decreased from 0.0066 ° / s and 0.0055 ° / s to 0.0011 ° / s ; and, benefiting from the threshold denoising based on improved CEEMDAN, the angle random walks decreased from 1.18 × 10 − 4 ° / s 1 / 2 and 2.04 × 10 − 4 ° / s 1 / 2 to 2.19 × 10 − 5 ° / s 1 / 2 , respectively.
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