New Methods of Parameter and State Estimation: A Comprehensive Guide
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5 out of 5
Language | : | English |
File size | : | 10651 KB |
Text-to-Speech | : | Enabled |
Screen Reader | : | Supported |
Enhanced typesetting | : | Enabled |
Word Wise | : | Enabled |
Print length | : | 371 pages |
In the realm of engineering, accurate estimation of parameters and states is crucial for optimal system performance and control. This book, "New Methods of Parameter and State Estimation," serves as an authoritative guide, providing a comprehensive overview of cutting-edge techniques and their applications in various domains.
Master the Art of System Identification
The first section of the book delves into the fundamentals of system identification, a critical step in model building for control and estimation. You will learn about:
- Dynamic models and their representation
- Data acquisition and preprocessing techniques
- Parameter estimation methods, including least squares, maximum likelihood, and Bayesian approaches
With a solid foundation in system identification, you will be equipped to accurately capture the behavior of complex systems and predict their future states.
Adaptive Control: Unleash the Power of Self-Tuning
The second section explores the principles of adaptive control, where controllers adjust their parameters in real-time based on system behavior. Key topics covered include:
- Model reference adaptive control (MRAC)
- Self-tuning regulators (STRs)
- Gain-scheduled control
By mastering adaptive control techniques, you will empower systems with the ability to handle uncertainties, nonlinearities, and time-varying conditions, ensuring optimal performance even in challenging environments.
Kalman Filtering: A Cornerstone of Modern Estimation
The final section of the book focuses on the renowned Kalman filter, a powerful estimation technique widely used in navigation, robotics, and signal processing. You will delve into:
- State space models and their properties
- Recursive estimation using the Kalman filter
- Extended Kalman filter (EKF) for nonlinear systems
With a deep understanding of Kalman filtering, you will be able to accurately estimate the states of dynamic systems even in the presence of noise and uncertainties.
Real-World Applications: Bridging Theory and Practice
Throughout the book, numerous real-world examples and case studies illustrate the practical applications of parameter and state estimation methods. These include:
- Control of robotic manipulators
- Navigation systems for autonomous vehicles
- Monitoring and fault detection in industrial processes
By connecting theoretical concepts to real-world challenges, you will gain a practical understanding of how these methods enhance system performance and safety.
Key Features:
- Comprehensive coverage of parameter and state estimation techniques
- Clear and concise explanations with mathematical rigor
- Up-to-date information on the latest advancements
- Abundant examples and case studies for practical insights
- Suitable for graduate students, researchers, and practicing engineers
:
"New Methods of Parameter and State Estimation" is an indispensable resource for anyone seeking to enhance their expertise in this critical field. Whether you are a graduate student, researcher, or practicing engineer, this book will provide you with the knowledge and tools necessary to excel in the design and implementation of state-of-the-art estimation systems.
5 out of 5
Language | : | English |
File size | : | 10651 KB |
Text-to-Speech | : | Enabled |
Screen Reader | : | Supported |
Enhanced typesetting | : | Enabled |
Word Wise | : | Enabled |
Print length | : | 371 pages |
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5 out of 5
Language | : | English |
File size | : | 10651 KB |
Text-to-Speech | : | Enabled |
Screen Reader | : | Supported |
Enhanced typesetting | : | Enabled |
Word Wise | : | Enabled |
Print length | : | 371 pages |