000			04182cam a22004337i 4500
001			18470898
003			OSt
005			20210930200612.0
008			150130s2015 ja a b 001 0 eng d
010			_a 2015932242
020			_a9784431553021 (alk. paper)
020			_a4431553029 (alk. paper)
035			_a(OCoLC)ocn900446275
040			_aBTCTA _beng _cBTCTA _erda _dYDXCP _dLYU _dDLC
042			_alccopycat
050	0	0	_aQA280 _b.O38 2015
082	0	4	_a519.5/5 _223
100	1		_aOhtsu, Kohei, _eauthor.
245	1	0	_aTime series modeling for analysis and control : _badvanced autopilot and monitoring systems / _cKohei Ohtsu, Hui Peng, Genshiro Kitagawa.
264		1	_aTokyo ; _aNew York : _bSpringer, _c[2015]
300			_aix, 119 pages : _billustrations (some color) ; _c23 cm
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
490	1		_aSpringerBriefs in statistics
490	1		_aJSS research series in statistics
504			_aIncludes bibliographical references and index.
505	0		_aCh1 Introduction (1.1 Necessity of statistical modeling for complex, large systems -- 1.2 Model of ship motion and main engine -- 1.3 Experimental ships and outline of topics discussed in remaining chapters) -- Ch2 Time series analysis through AR modeling (2.1 Univariate time series analysis through AR modeling -- 2.2 Analysis of ship motion through univariate AR modeling -- 2.3 Multivariate AR modeling of controlled systems -- 2.4 Power contribution analysis of a feedback system -- 2.5 State-space model and Kalman filter -- 2.6 Piecewise stationary modeling -- 2.7 Model-based monitoring system -- 2.8 RBF-ARX modeling for a nonlinear system) -- Ch3 Design of a model-based autopilot system for course keeping motion (3.1 Statistical optimal controller based on the ARX model -- 3.2 AR model-based autopilot system -- 3.3 Rudder-roll control system -- 3.4 Application to the marine main engine governor system) -- Ch4 Advanced autopilot systems (4.1 Noise-adaptive autopilot system -- 4.2 RBF-ARX model-based predictive control -- 4.3 GPS signal-based computation of a ship's tracking error and course deviation -- 4.4 Tracking control approach to marine vehicles).
520			_aThis book presents multivariate time series methods for the analysis and optimal control of feedback systems. Although ships' autopilot systems are considered through the entire book, the methods set forth in this book can be applied to many other complicated, large, or noisy feedback control systems for which it is difficult to derive a model of the entire system based on theory in that subject area. The basic models used in this method are the multivariate autoregressive model with exogenous variables (ARX) model and the radial bases function net-type coefficients ARX model. The noise contribution analysis can then be performed through the estimated autoregressive (AR) model and various types of autopilot systems can be designed through the state space representation of the models. The marine autopilot systems addressed in this book include optimal controllers for course-keeping motion, rolling reduction controllers with rudder motion, engine governor controllers, noise adaptive autopilots, route-tracking controllers by direct steering, and the reference course-setting approach. The methods presented here are exemplified with real data analysis and experiments on real ships. This book is highly recommended to readers who are interested in designing optimal or adaptive controllers not only of ships but also of any other complicated systems under noisy disturbance conditions. -- _cSource other than Library of Congress.
650		0	_aTime-series analysis.
650		0	_aControl theory _xStatistical methods.
700	1		_aPeng, Hui, _eauthor.
700	1		_aKitagawa, G. _q(Genshiro), _d1948-, _eauthor.
830		0	_aSpringerBriefs in statistics.
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2lcc _cBK
999			_c6725 _d6725