Time Series Modeling Analysis & Control, Advanced Autopilot & Monitoring Systems

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Item specifics

Condition
Like New: A book in excellent condition. Cover is shiny and undamaged, and the dust jacket is ...
Book Title
Time Series Modeling for Analysis and Control : Advanced Autopilo
Item Height
.5 in
Educational Level
Adult & Further Education
Level
Advanced
ISBN
9784431553021
Category

About this product

Product Identifiers

Publisher
Springer Japan
ISBN-10
4431553029
ISBN-13
9784431553021
eBay Product ID (ePID)
204190807

Product Key Features

Number of Pages
IX, 119 Pages
Language
English
Publication Name
Time Series Modeling for Analysis and Control : Advanced Autopilot Systems for Ships
Subject
Mathematical & Statistical Software, Probability & Statistics / General, Probability & Statistics / Time Series, Applied
Publication Year
2015
Type
Textbook
Author
Hui Peng, Genshiro Kitagawa, Kohei Ohtsu
Subject Area
Mathematics, Computers
Series
Springerbriefs in Statistics Ser.
Format
Trade Paperback

Dimensions

Item Weight
83.1 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2015-932242
Dewey Edition
23
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
519.5/5
Table Of Content
Ch1 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).
Synopsis
This 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.
LC Classification Number
QA276-280

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