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Comparison of DEAS and GA for Sensitivity Optimization in MEMS Gyroscope

Authors:
Hyunhak Cho
Moonho Park
Jaeyong Kim
Sungshin Kim

Keywords: DEAS, GA, Gyroscope, AGV

Abstract:
This paper is research into how to optimize the sensitivity values of an installed gyroscope in the autonomous guided vehicle with a magnet-gyro guided system. A magnet-gyro guided system mostly uses a MEMS gyroscope, which is small-sized, uses little power, and costs little. However, the MEMS gyroscope needs a high sensitivity value for changing angular velocity in each environment, not only due to the necessity of an accurate sensitivity value for the measured angle value but also due to the difference between the measured angle and sensitivity value. The sensitivity value describes the specifications of the sensor, but the sensitivity value is influenced by the given environment or gradient. Therefore, the optimization process is required for the sensitivity value of the installed gyroscope in the environment. A number of optimization algorithms have been studied, but we chose the Dynamic Encoding Algorithm for Searches (DEAS) and the Genetic Algorithm (GA) to optimize the sensitivity value. We used an AGV with laser navigation for experiments in this paper. We did 5 experiments for each change of the rotation angle - 30, 40, 50, 60° - and compared the calculations of the sensitivity value of optimization through the DEAS and the GA. The experiment results confirm that the optimization sensitivity values of the DEAS contain less error than the optimization sensitivity value by the GA algorithm.

Pages: 33 to 38

Copyright: Copyright (c) IARIA, 2014

Publication date: June 22, 2014

Published in: conference

ISSN: 2308-4065

ISBN: 978-1-61208-352-0

Location: Seville, Spain

Dates: from June 22, 2014 to June 26, 2014