We present a novel silicon microgyroscope (SMG) temperature prediction and control system in a narrow space. As the temperature of SMG is closely related to its drive mode frequency and driving voltage, a temperature prediction model can be established based on the BP neural network. The simulation results demonstrate that the established temperature prediction model can estimate the temperature in the range of −40 to 60 °C with an error of less than ±0.05 °C. Then, a temperature control system based on the combination of fuzzy logic controller and the increment PID control method is proposed. The simulation results prove that the Fuzzy-PID controller has a smaller steady state error, less rise time and better robustness than the PID controller. This is validated by experimental results that show the Fuzzy-PID control method can achieve high precision in keeping the SMG temperature stable at 55 °C with an error of less than 0.2 °C. The scale factor can be stabilized at 8.7 mV/°/s with a temperature coefficient of 33 ppm °C−1. ZRO (zero rate output) instability is decreased from 1.10°/s (9.5 mV) to 0.08°/s (0.7 mV) when the temperature control system is implemented over an ambient temperature range of −40 to 60 °C.

In this work we investigate the possibility of applying the adaptive control algorithm to Micro-Electro-Mechanical System (MEMS) gyroscopes. Through comparing the gyroscope working conditions with the reference model, the adaptive control method can provide online estimation of the key parameters and the proper control strategy for the system. The digital second-order oscillators in the reference model are substituted for two phase locked loops (PLLs) to achieve a more steady amplitude and frequency control. The adaptive law is modified to satisfy the condition of unequal coupling stiffness and coupling damping coefficient. The rotation mode of the gyroscope system is considered in our work and a rotation elimination section is added to the digitalized system. Before implementing the algorithm in the hardware platform, different simulations are conducted to ensure the algorithm can meet the requirement of the angular rate sensor, and some of the key adaptive law coefficients are optimized. The coupling components are detected and suppressed respectively and Lyapunov criterion is applied to prove the stability of the system. The modified adaptive control algorithm is verified in a set of digitalized gyroscope system, the control system is realized in digital domain, with the application of Field Programmable Gate Array (FPGA). Key structure parameters are measured and compared with the estimation results, which validated that the algorithm is feasible in the setup. Extra gyroscopes are used in repeated experiments to prove the commonality of the algorithm.

-A new digitized decoupled dual-axis micro dynamically tuned gyroscope with three equilibrium rings (TMDTG) is proposed which can eliminate the constant torque disturbance (CTD) caused by the double rotation frequency of a driving shaft with a micro dynamically tuned gyroscope with one equilibrium ring (MDTG). A mechanical and kinematic model of the TMDTG is theoretically analyzed and the structure parameters are optimized in ANSYS to demonstrate reliability. By adjusting the thickness of each equilibrium ring, the CTD can be eliminated. The digitized model of the TMDTG system is then simulated and examined using MATLAB. Finally, a digitized prototype based on FPGA is created. The gyroscope can be dynamically tuned by adjusting feedback voltage. Experimental results show the TMDTG has good performance with a scale factor of 283 LSB/ o /s in X-axis and 220 LSB/ o /s in Y-axis, respectively. The scale factor non-linearity is 0.09% in X-axis and 0.13% in Y-axis. Results from analytical models, simulations, and experiments demonstrate the feasibility of the proposed TMDTG.