Abstract
This document details the implementation and test of a self-calibrating estimation architecture for the sideslip of a Formula Student prototype. The proposed algorithm fuses several sensors being the most relevant an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS). It is presented a comparison between a linear and a non-linear estimators, and their consequences. The algorithm is tested with real data from a Formula Student vehicle, and validated with a differential GPS. It is also reported an implementation of the proposed algorithm in a micro-controller, and tested with a radio-controlled (RC) vehicle. These results are also validated with the data from a more accurate indoor motion system.
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