Authors

• P. Heydari
• H. Khaloozadeh
• A.P. Heydari

Abstract

In this paper statistical and time series models are used for determining the random drift of a dynamically Tuned Gyroscope (DTG). This drift is compensated with optimal predictive transfer function. Also nonlinear neural-network and fuzzy-neural models are investigated for prediction and compensation of the random drift. Finally the different models are compared together and their advantages are discussed

Keywords

• Dynamically Tuned Gyroscope
• Random Drift
• Time series methods
• Neural-Networks
• Fuzzy logic
• Error compensation