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Time Series Modeling for Analysis and Control

Part of the SpringerBriefs in Statistics Book Series

DOI: 10.1007/978-4-431-55303-8

ISBN: 978-4-431-55302-1

Publisher: Springer Japan - Springer Journals

Mar 20, 2015

Available

Introduction

Ohtsu, Kohei; Peng, Hui; Kitagawa, Genshiro

Pages: 1 –6

[In the following, the necessity of statistical modeling for analysis and control of complex, large systems with large disturbances and the aim of this book are first presented. We then present the basic concepts of ship motion and course keeping control problems, which are the primary...
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Time Series Analysis Through AR Modeling

Ohtsu, Kohei; Peng, Hui; Kitagawa, Genshiro

Pages: 7 –56

[The features of dynamic phenomena can be described using time series models. In this chapter, we present various types of autoregressive models for the analysis of time series, such as univariate and multivariate autoregressive models, an autoregressive model with exogenous variables, a locally...
Available

Design of a Model-Based Autopilot System for Course Keeping Motion

Ohtsu, Kohei; Peng, Hui; Kitagawa, Genshiro

Pages: 57 –81

[A critical problem in applying the optimal control theory to a large-scale complex system that is subject to large disturbances, such as a ship, an electric power plant, or a large chemical plant, is that it is sometimes difficult to obtain a precise state-space model from the theory of the...
Available

Advanced Autopilot Systems

Ohtsu, Kohei; Peng, Hui; Kitagawa, Genshiro

Pages: 83 –115

[In the previous chapter, we presented three types of autopilot system based on the stationary linear AR model. However, actual sea conditions may change gradually or abruptly due to various factors, and in such a situation, we must consider a nonstationary time series. Furthermore, it may become...

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