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Autonomous Underwater Environmental Robot Motion Control System Simulation

Posted on:2004-12-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y M LiuFull Text:PDF
GTID:2208360095451361Subject:Control theory and control engineering
Abstract/Summary:PDF Full Text Request
China is a country with a vast territory and extensive lake land. These freshwater lakes contain vast biological and freshwater resources. But, many of them are polluted to various degrees now, and do great harm to human' s health. So the water quality of them must be investigated and understood so that they can be wisely developed and properly protected. This fact promotes the development of unmanned underwater vehicles for inspection and monitoring of the freshwater lake environment.In this paper, we give a brief introduction to the structure of an autonomous underwater vehicle (AUV) for environmental protection firstly, secondly we discuss the control system of the AUV, thirdly discusses the way of real-time path planning for AUV by dynamic programming, finally we simulate the proposed control system and the path planning method by means of computer and give the simulation results of it. The last three parts are the main work of the research.This AUV for environmental protection has three degrees of freedom, called surge, heave and yaw. The control of AUV has been a challenge to control engineer due to combined non-linear nature of both the vehicle itself and the environment in which they operate. We use PID control and fuzzy decision to fulfill the motion trajectory control. This AUV are designed to have three thrusters, two horizontal thrusters are used to surge and yaw, one vertical thruster is used to heave. With the help of path planning, the AUV can avoid the obstacle autonomously.The control system of the AUV for environmental protection has been successfully simulated. The simulation results demonstrate the good performance of the proposed control system.
Keywords/Search Tags:autonomous underwater vehicle for environmental protection, PID, fuzzy decision making, dynamic programming, simulation
PDF Full Text Request
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