A Kalman Filter based Sensor Fusion Technique for Balancing a 2-Wheel System
The objective of the presented work is to design and
implement a sensor fusion algorithm using Kalman Filter for
balancing the system on 2-wheels. The system uses inertial sensors
such as 3-axis linear accelerometer and dual-axis gyroscope to
calculate the tilt for balancing. The estimation algorithm i.e. Kalman
filter continuously and recursively corrects the values obtained by
mathematical integration of the velocity, measured using gyroscope at
the rate of 20Hz. The correction is performed using the inclination
value obtained from accelerometer. This reduces the integration drift
that originates from errors in the angular velocity signal. In addition,
the gyroscope offset is continuously calibrated. The tilt estimated by
the Kalman filter is given to PID algorithm with a reference of 0
radian, to balance the system. The result shows the need of Kalman
filter to remove sensor noise. The control and filter algorithm are
implemented on Atmega32 microcontroller. This study reinforces the
significance of sensor fusion for optimum performance. The
conception presented in this paper will be of assistance in existing
applications and in new designs.
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Mr. Suryawanshi is a member of various professional societies like IEEE,
International Association of Engineers, Systems Society of India, Instrument
Society of India, Institution of Engineers, to name a few.
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