Thảo luận:Sáu căn bệnh của giới nghiên cứu Trung Quốc
Trông người lại ngẫm đến ta.
Cha`o ca'c ba'c,
Co' vu. na`y xin muo^'n trao ddo^?i cu`ng ca'c ba'c! Ho^m qua to^i pha't hie^.n ra mo^.t ba`i ba'o du+. ho^.i nghi. va` dda(ng ky? ye^'u ho^.i nghi. IEEE Workshop in Advanced Motion Control 2004 (AMC2004):
An optimal ship autopilot using a multivariate auto-regressive exogenous model Nguyen, M.-M.; Nguyen, T.-P.; Duc-Luong Tran; Nguyen, T.-K.; Quang-Trung Nguyen; Van-Phuong Dang; Van-Long Tran; Nguyen, D.-H.; Nguyen, T.-M.-N.; Anh-Dung Mai Advanced Motion Control, 2004. AMC apos; 04. The 8th IEEE International Workshop on Volume, Issue , 25-28 March 2004 Page(s): 701 - 706
Digital Object Identifier 10.1109/AMC. 2004.1297954
Summary: Linear Quadratic Gaussian (LQG) control algorithm linked to Recursive Least Squares (RLS) algorithm has been applied to a multivariate auto-regressive exogenous (MARX) model of ships to construct a ship autopilot. It has been found from computer simulation and full-scale experiments aboard a training ship that the autopilot is robust and has good features in both course keeping and course changing.
[PDF] An optimal ship autopilot using a multivariate auto-regressive ... File Format: PDF/Adobe Acrobat
Shioji Maru. Table 3: Particular dimension of. Shioji Maru. 4.1. Real-time Control System aboard ... Shioji Maru. A representative full-scale experiment is ... ieeexplore.ieee. org/iel5/ 9091/28850/ 01297954. pdf - Similar pages - Note this
Ba`i ba'o na`y co' the^? ddu+o+.c coi la` copy nguye^n va(n tu+` ba`i ba'o cu?a bo.n to^i tham du+. IFAC (International Federation of Automatic Control) Workshop on Control Applications of Optimization 2000 (CAO2000):
Nguyen, H.D., D.M. Le, and K. Ohtsu (2000). Ship's Optimal Autopilot with a Multivariate Auto-Regressive eXogenous Model. Proceedings of the 11th IFAC Workshop on Control Applications of Optimization (CAO2000), St. Petersburg, Russia.
Pha^`n dda^`u ba?n go^'c nhu+ sau:
SHIP'S OPTIMAL AUTOPILOT WITH A MULTIVARIATE AUTO-REGRESSIVE EXOGENOUS MODEL
Duc-Hung Nguyen*, Minh-Duc Le** and Kohei Ohtsu*
- Ship Maneuvering Laboratory, Tokyo University of Mercantile Marine
2-1-6 Etchyujima, Koto-ku, Tokyo 135-8533, Japan. Tel & Fax: +81-3-5245-7389. Email: hnguyen@ipc. tosho-u.ac. jp, ohtsu@ipc.tosho- u.ac.jp
-
- Graduate School of Engineering, Hiroshima University. 1-4-1 Kagamiyama,
Higashi Hiroshima-shi, Hiroshima 739-8527, Japan Mobile Tel: +81-070-5671- 2114. Email: melinh@ipc.hiroshim a-u.ac.jp
Abstract: This paper presents a new application of the linear quadratic gaussian (LQG) control algorithm linked to the recursive least squares (RLS) algorithm applied to a multivariate auto-regressive exogenous (MARX) model of ship to construct an autopilot for steering ship. Simulation performed for a training ship is described. As the first step of designing a tracking system, the optimal autopilot with the MARX model was used to keep and change the ship's course during full-scale experiments aboard the training ship. It has been found that the autopilot has robustness and good performance for steering ship. Copyright © 2000 IFAC
Keywords: estimation and identification, ship steering dynamics, quadratic optimal control, control design.
So sa'nh hai ba`i chi? tha^'y va`i ddie^?m kha'c ra^'t nho?:
1. Te^n ddo^?i chu't ddi?nh (ship's -> a, va` with = using) 2. Abstract ddu+o+.c su+?a ddi chu't ddi?nh 3. Citation - References: ddo^?i tu+` Harvard referencing system trong ba`i cu?a to^i tha`nh he^. tho^'ng tham kha?o dda'nh so^'.
Ca'c ba'c co' the^? so sa'nh hai ba`i:
http://www.dieukhie n.net/downloads/ CBB/HaiBaiBao /OriginalManuscript_ CAO2000.pdf http://www.dieukhie n.net/downloads/ CBB/HaiBaiBao/PlagiarisedPaper20 04.pdf
Vu. na`y ca'c ba'c go'p y' ca^`n pha?i la`m sa'ng to? hay kho^ng? Theo to^i thi` su+. trung thu+.c cu?a ngu+o+`i la`m nghie^n cu+'u khoa ho.c quan tro.ng ho+n ta^'t ca?. Ne^'u nhu+~ng ngu+o+`i dda.o va(n na`y tro+? tha`nh ca'c tie^'n sy~, tro+? tha`nh ca'c tha`y dda.i ho.c hoa(.c tro+? tha`nh ca'c ca'n bo^. la~nh dda.o thi` ca'i dda^'t nu+o+'c VN na`y se~ ddi dde^'n dda^u va` ne^`n khoa ho.c VN se~ ddi dde^'n dda^u???
Mo+`i ca'c ba'c dda'nh gia' giu`m vu. na`y.
H.
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