Model-Based Monitoring and Statistical Control
Author | : Kohei Ohtsu |
Publisher | : CRC Press |
Total Pages | : 467 |
Release | : 2024-06-11 |
ISBN-10 | : 9781040036051 |
ISBN-13 | : 1040036058 |
Rating | : 4/5 (058 Downloads) |
Download or read book Model-Based Monitoring and Statistical Control written by Kohei Ohtsu and published by CRC Press. This book was released on 2024-06-11 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: Available in English for the first time, this classic and influential book by the late Kohei Ohtsu presents real examples of ships in motion under irregular ocean waves, how to understand the characteristics of fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling. It also explains how to realize prediction and optimal control based on time series models. In recent years, the need to improve safety and reduce environmental impact in ship operations has been increasing, and the statistical methods presented in this book will be increasingly needed in the future. In addition, the recent development of innovative AI technology and highspeed communications will make it possible to adapt this method not only to ship monitoring and control, but also to any field that involves irregular fluctuations, and it is expected to contribute to solving issues that have been difficult to solve in the past. Part 1 describes classical spectral method for the analysis of stochastic phenomena. In Part 2, this book explains methods to construct time series models using the information criterion, to capture the characteristics of ship and engine motions using the model, to design a model-based monitoring system that informs navigators operating the ship and managers ashore. Furthermore, it explains statistical control method to design an autopilot system and the governor of a marine engine, while showing actual examples. Part 3 presents the basic knowledge necessary for understanding these topics of the book, namely, the basic theory of ship motion, probability and statistics, Kalman filter and statistical optimal control theory.