Log In
Or create an account ->
Imperial Library
Home
About
News
Upload
Forum
Help
Login/SignUp
Index
Cover image
Title page
Table of Contents
Copyright
List of Contributors
Dedication
About the Editors
Preface
Acknowledgment
Chapter 1: Hierarchical Dynamic Neural Networks for Cascade System Modeling With Application to Wastewater Treatment
Abstract
1.1. Introduction
1.2. Cascade Process Modeling Via Hierarchical Dynamic Neural Networks
1.3. Stable Training of the Hierarchical Dynamic Neural Networks
1.4. Modeling of Wastewater Treatment
1.5. Conclusions
References
Chapter 2: Hyperellipsoidal Neural Network Trained With Extended Kalman Filter for Forecasting of Time Series
Abstract
2.1. Introduction
2.2. Mathematical Background
2.3. HNN for Time Series Forecasting
2.4. Results
2.5. Conclusion
References
Chapter 3: Neural Networks: A Methodology for Modeling and Control Design of Dynamical Systems
Abstract
3.1. Introduction
3.2. Neural Modeling and Control for Discrete-Time Systems
3.3. Neural Modeling and Control for Continuous-Time Systems
3.4. Further NN Applications
3.5. Conclusions
References
Chapter 4: Continuous-Time Decentralized Neural Control of a Quadrotor UAV
Abstract
4.1. Introduction
4.2. Fundamentals
4.3. Neural Backstepping Controller Design
4.4. Results
4.5. Conclusion
References
Chapter 5: Adaptive PID Controller Using a Multilayer Perceptron Trained With the Extended Kalman Filter for an Unmanned Aerial Vehicle
Abstract
5.1. Introduction
5.2. Kalman Filter
5.3. MLP Trained With the EKF
5.4. UAV Controlled With an MLP
References
Chapter 6: Support Vector Regression for Digital Video Processing
Abstract
6.1. Introduction
6.2. Support Vector Regression
6.3. SVR Method
6.4. Results
6.5. Conclusions
References
Chapter 7: Artificial Neural Networks Based on Nonlinear Bioprocess Models for Predicting Wastewater Organic Compounds and Biofuel Production
Abstract
7.1. Introduction
7.2. Activated Sludge Process
7.3. Anaerobic Digestion Process
7.4. Conclusion
References
Chapter 8: Learning-Based Identification of Viral Infection Dynamics
Abstract
Acknowledgements
8.1. Introduction
8.2. Neural Identification
8.3. Within-Host Influenza Infection
8.4. Within-Host HIV Infection
8.5. Numerical Results
8.6. Conclusions
References
Chapter 9: Attack Detection and Estimation for Cyber-Physical Systems by Using Learning Methodology
Abstract
9.1. Introduction
9.2. Background on System Modeling and Attacks
9.3. Secure Linear Networked Control Systems
9.4. Secure Nonlinear Networked Control Systems
9.5. Results and Discussion
9.6. Conclusions
References
Chapter 10: Sensitivity Analysis With Artificial Neural Networks for Operation of Photovoltaic Systems
Abstract
10.1. Introduction
10.2. Experimental Facility and Database
10.3. Sensitivity Analysis
10.4. Application
10.5. Conclusions
References
Chapter 11: Pattern Classification and Its Applications to Control of Biomechatronic Systems
Abstract
11.1. Introduction
11.2. Biomechatronic System Components
11.3. Biomechatronic System Proposed
11.4. Conclusion
References
Index
← Prev
Back
Next →
← Prev
Back
Next →