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논문 기본 정보

자료유형
학술저널
저자정보
Dong-Dong Mu (Dalian Maritime University) Guo-Feng Wang (Dalian Maritime University) Yun-Sheng Fan (Dalian Maritime University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.12 No.6
발행연도
2017.11
수록면
2,365 - 2,377 (13page)

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초록· 키워드

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This paper addresses two interrelated problems concerning the tracking control of pod propulsion unmanned surface vessel (USV), namely, the modeling of pod propulsion USV, and tracking controller design. First, based on MMG modeling theory, the model of pod propulsion USV is derived. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network approximation and adaptive method. Meanwhile, unlike some existing tracking methods for surface vessel whose control algorithms suffer from “explosion of complexity”, a novel neural shunting model is introduced to solve the problem. Using a Lyapunov functional, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of pod propulsion USV is proved; second, the neural shunting model is used to solve the problem of “explosion of complexity”, and this is a combination of knowledge in the field of biology and engineering; third, the developed controller is able to capture the uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. Numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.

목차

Abstract
1. Introduction
2. Modeling of Pod Propulsion USV
3. Problem Formulation and Preliminaries
4. Control Design
5. Stability Analysis
6. Numerical Simulations
7. Conclusion
References

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