NDLI: Adaptive wind feedforward control of an Unmanned Surface Vehicle for station keeping

Content Provider	IEEE Xplore Digital Library
Author	Qu, Huajin von Ellenrieder, Karl D.
Copyright Year	2015
Description	Author affiliation: Department of Ocean & Mechanical Engineering, Florida Atlantic University, 101 N. Beach Rd. Dania Beach, USA (Qu, Huajin; von Ellenrieder, Karl D.)
Abstract	Unmanned Surface Vehicles (USVs) have widespread commercial, scientific and military applications. In some of these applications station keeping is essential. Since USVs have a bigger surface/ weight ration than large commercial ships, they are more sensitive to wind disturbances, especially during station keeping. The modeling, identification and control of a 4.9 meter long, 180 kilogram wave adaptive modular vehicle (WAM-V) USV are presented in this paper. The propulsion system of the USV is custom designed with two azimuthing thrusters, making the USV fully actuated. System identification tests were conducted to get the precise model of the USV. A sliding mode controller was first applied to the USV and a wind feedforward controller was designed to aid the nonlinear feedback control to mitigate wind disturbance. For the feedforward controller design, a wind model was formulated that uses the apparent wind speed and direction collected from a high accuracy anemometer. A model based adaptive mechanism was developed to tune the feedforward control gains for the best performance. Station keeping field tests were conducted at a location with an average wind speed of 9 knots. The results show that with the tuned feedforward controller, the USV can hold its position and heading better over extended periods of time than a single feedback controller.
Starting Page	1
Ending Page	10
File Size	2208313
Page Count	10
File Format	PDF
ISBN	9780933957435
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-10-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	MTS
Subject Keyword	Feedforward neural networks Vehicles Wind speed Marine vehicles Propulsion Fluid flow measurement Sea surface automatic tuning Wind Feedforward Control Unmanned Surface Vehicles Station Keeping
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Wind feed-forward control of a USV

Development of a USV station-keeping controller

Autopilot design for a robotic unmanned surface vehicle

Adaline neural network for online self-learning and adaptive control of a vehicle with thrusters in a fluid

A feedforward neural network for identification and adaptive control of autonomous underwater vehicles

Combined speed and yaw control of underactuated unmanned surface vehicles

Design and analysis of CentrUMS-ITB unmanned semi-submersible vehicle

Ocean flow measurement using an autonomous underwater vehicle

Station-Keeping Control of an Unmanned Surface Vehicle Based on the Wind Direction Mesurement

Adaptive wind feedforward control of an Unmanned Surface Vehicle for station keeping

Similar Documents

Wind feed-forward control of a USV

Development of a USV station-keeping controller

Autopilot design for a robotic unmanned surface vehicle

Adaline neural network for online self-learning and adaptive control of a vehicle with thrusters in a fluid

A feedforward neural network for identification and adaptive control of autonomous underwater vehicles

Combined speed and yaw control of underactuated unmanned surface vehicles

Design and analysis of CentrUMS-ITB unmanned semi-submersible vehicle

Ocean flow measurement using an autonomous underwater vehicle

Station-Keeping Control of an Unmanned Surface Vehicle Based on the Wind Direction Mesurement

Adaptive wind feedforward control of an Unmanned Surface Vehicle for station keeping