Hardware Platforms for Electrostatic Tuning of Mems Gyroscope Using Nature-Inspired Computation
We propose a tuning method for Micro-Electro-Mechanical Systems (MEMS) gyroscopes based on evolutionary computation to increase the accuracy of MEMS gyroscopes through electrostatic tuning. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation. We also report on the development and preliminary results of a hardware platform for integrated tuning based on “switched drive-angle” of MEMS gyroscopes whereby the same gyro is operated with its drive direction first at 0° and then at 90°. The control of this device is implemented through a digital design on a Field Programmable Gate Array (FPGA). The hardware platform easily transitions to an embedded solution that allows for the miniaturization of the system to a single chip.
Key wordsMEMS tuning genetic algorithm simulated annealing FPGA
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