Optimal Control Of Autonomous Underwater Vehicle (AUV) Using Genetic Algorithms

Lee , Huey Yee (2010) Optimal Control Of Autonomous Underwater Vehicle (AUV) Using Genetic Algorithms. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

This thesis describes the optimal control of autonomous underwater vehicle (AUV) with Genetic Algorithms (GA) Optimization. Due to the harsh and unstable condition of underwater environment, the demand of AUV in underwater exploration field is increasing rapidly. AUV use in this project is low cost, small and light. Thus, it is more unstable compare to other huge sized AUV. Its stability is easily affected by several factors, such as underwater wave current and other unpredicted underwater condition. As a result, the process of capturing data is more difficult and the quality of data obtained is low and inaccurate. . Objective in this project is to overcome the current weaknesses, by implementing GA in Matlab environment for stability control and obstacle avoidance purpose. Genetic algorithm is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Besides, fitness functions are developed in order to optimize the movement of AUV. Initially, analysis of the fitness function developed is done by using some data create manually. Data generated from the sensors will be fed to GA and applied it into fitness functions. The best fitness value will be fed back to AUV in order to control the motors propulsion force. By implementing GA, AUV able to maintain its stability, avoid obstacles and also travels at the certain distance from the seabed. The fitness functions of the stability problem and simulation results are presented in this thesis.

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