Time Series Modeling for Analysis and Control Advanced Autopilot and Monitoring Systems /
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 system...
| Κύριοι συγγραφείς: | , , |
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| Συγγραφή απο Οργανισμό/Αρχή: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Tokyo :
Springer Japan : Imprint: Springer,
2015.
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| Σειρά: | SpringerBriefs in Statistics,
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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).
