Predictive Digital Twins
Foundations and Applications
- 1 Edición - 1 de marzo de 2027
- Última edición
- Autor: Agus Hasan
- Idioma: Inglés
Predictive Digital Twins: Foundations and Applications addresses the theoretical foundations, practical applications, and emerging trends associated with predictive digital tw… Leer más
Descripción
Descripción
Predictive Digital Twins: Foundations and Applications addresses the theoretical foundations, practical applications, and emerging trends associated with predictive digital twins. With a specific focus on predictive capabilities, digital twins developed for this purpose are commonly referred to as predictive digital twins. Despite the growing recognition of their importance, the literature on predictive digital twins remains fragmented, with a lack of comprehensive resources covering the concept systematically. This gap is particularly evident in academia, where, as a university professor teaching a master's course on digital twins, I have identified a need for a dedicated reference book that provides students with a structured and in-depth exploration of predictive digital twins.
This book addresses this gap by providing students, researchers, and practitioners with a valuable resource to enhance their understanding of this emerging concept. Digital twins are a pivotal technology in the ongoing Industry 4.0 revolution, with one of their most significant advantages being their ability to provide accurate predictions.
Puntos claves
Puntos claves
- Provides clear explanations of the fundamental concepts, theories, and technologies underpinning predictive digital twins to support effective teaching and research.
- Includes real-world applications and case studies illustrating the practical implementation of predictive digital twins across different industries.
- Offers practical insights into the development and implementation of predictive digital twins for process optimization and predictive maintenance.
- Provides guidance on best practices for designing, developing, managing, and optimizing predictive digital twin systems.
- Bridges theoretical foundations and practical applications, making the book accessible to students, researchers, and industry practitioners.
De interès para
De interès para
Índice
Índice
1.1 Definition, history, and typology
1.2 Digital twins in the context of industry 4.0
2. Fundamental aspects of predictive digital twins
2.1 Key components and characteristics
2.2 The role of predictive digital twins
2.3 Challenges and opportunities
3. Modelling and simulation of dynamic systems
3.1 Principle of dynamic systems modelling
3.2 Discretization and simulation techniques
3.3 Applications in digital twins
3.4 Exercise
4. State and parameter estimation
4.1 State and parameter estimation problems
4.2 Deterministic approach using adaptive observer
4.3 Stochastic approach using adaptive Kalman filter
4.4 Exercise
5. Sensor and actuator fault diagnosis
5.1 Fault diagnosis problems
5.2 Actuator fault diagnosis
5.3 Sensor fault diagnosis
5.4 Exercise
6. Data-driven discovery of governing equations
6.1 Inverse problem
6.2 Methodology
6.3 Exercise
7. Prediction methods for digital twins
7.1 Predictions methods in digital twins
7.2 Exercise
8. Model-based predictive digital twins
8.1 Model-based predictions
8.2 Exercise
9. Data-driven predictive digital twins
9.1 Data-driven predictions
9.2 Exercise
10. Case study I: predictive digital twins for autonomous marine vessels
11. Case study II: predictive digital twins for unmanned aerial vehicles
12. Case study III: predictive digital twins for wind energy applications
13. Case study IV: predictive digital twins for healthcare applications
14. Future of predictive digital twins
Detalles del producto
Detalles del producto
- Edición: 1
- Última edición
- Publicado: 1 de marzo de 2027
- Idioma: Inglés
Sobre el autor
Sobre el autor
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Agus Hasan
Agus Hasan is a professor in cyber-physical systems at department of ICT and natural sciences, Norwegian University of Science and Technology (NTNU). He received his PhD in cybernetics from department of cybernetics engineering, NTNU and BSc in mathematics from department of mathematics, Bandung Institute of Technology. His research interests are in the areas of system dynamics, digital twins, and autonomous systems. He is IEEE senior member and serves as IEEE technical committee member on aerial robotics and unmanned aerial vehicles and IFAC technical committee member on distributed parameter systems. He is a recipient of ASME Best Paper Award in Mechatronics in 2015.