Abstract
The research on underwater systems has gained enormous attention during the last two decades because of applications taking place in many fields. Therefore, the significant number of Unmanned Underwater Vehicles (UUVs) has been developed for solving the wide range of scientific and applied tasks of ocean research and development in the world. Guidance, navigation, and control techniques are key research and development areas for the success of those sophisticated UUV missions. One of the main objective of this chapter is to provides detailed explanations on the theory behind the main concepts that directly influence the design of the dynamic mathematical model of AUV and then to accomplish dynamic mathematical modeling of an AUV in MATLAB version 7.5 environment under different swimming conditions. In order to develop high fidelity AUV simulation model and implement control and navigation algorithm for the vehicle, we need to know overall AUV modeling. Another main focus of this chapter is to realize the parameter identification of hydrodynamic coefficients based on a Least Square Estimation (LSE) algorithm for a nonlinear mathematical modeling of AUV. Parameter Identification is very important to have the estimated values of these coefficients in order to accurately simulate the AUV.s dynamic performance. The estimated hydrodynamic coefficients can be used as inputs not only for a mathematical model to analyze the maneuvering performance but also for the AUV.s motion controller.
Original language | English |
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Title of host publication | Autonomous Vehicles |
Subtitle of host publication | Intelligent Transport Systems and Smart Technologie |
Publisher | Nova Science Publishers, Inc. |
Pages | 81-111 |
Number of pages | 31 |
ISBN (Electronic) | 9781633213265 |
ISBN (Print) | 9781633213241 |
Publication status | Published - 1 Jul 2014 |
Bibliographical note
Publisher Copyright:© 2014 by Nova Science Publishers, Inc. All rights reserved.
Keywords
- Autonomous Underwater Vehicle
- Dynamic Modeling
- Least Square Estimation
- Parameter Identification