Vibration Error Compensation Module for Autonomous Underwater Vehicle (AUV)

Abstract

This project study the Internal Measurement Unit (IMU) vibration error effect for Autonomous Underwater Vehicles (AUV). As the AUV propeller movement speed is induced by a non-uniformity in the flow, it will cause the shaft's propulsion to vibrate. Therefore, to ensure the AUV motion control is more reliable, the shaft vibration must be eliminated from the collected reading. This project reveals the feasible data of position and orientation for navigation, analyses observable errors and tests performance of proposed optimization techniques. The main objectives for this project are to identify the vibration error of the autonomous underwater vehicle (AUV) and integrate the vibration error compensation method for the navigation purpose using MATLAB. Using the filtering technique which is known as Extended Kalman Filter (EKF) IMU reading, the noise of the vibration error will be reduced. The Extended Kalman Filter is used as a system state indicator that uses a preview loop from persistent unregulated assumptions. Furthermore, a projection for the next state is predicted by using data obtained from previous and present states. This prediction is then updated and used based on the observation process, which focuses on estimates and measurements. The end-to-end RMS errors of no disturbance module for x, y and z are 1.17 meters, 0.99 meters and 0.03 meters. Moreover, the end-to-end RMS errors of present disturbance module for x, y and z are 0.57 meters, 0.53 meters and 0.68 meters. These updated estimates may be used with a new statistical calculation. This work will help the AUV to further improve the state estimation and navigation performance.