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Neural Networks for Robotics
The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost mapping, object recognition, intelligent control of ground and aerial robots, and clustering, with real-time implementations. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures.
Discrete-Time Neural Observers
Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of these schemes, the authors also present simulation and experimental results related to their application in meaningful areas, such as electric three phase induction motors and anaerobic process, which show ...
Robotics Software Design and Engineering
Robotics Software Design and Engineering is an edited volume on robotics. Chapters cover such topics as cognitive robotics systems, artificial intelligence, force feedback, autonomous driving embedded systems, multi-robot systems, a robot software framework for Real-time Control systems, and Industry 4.0. Also discussed are humanoid robots, aerial and work vehicles, and robot manipulators.
Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications
"This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.
Fuzzy Logic in Intelligent System Design
This book describes recent advances in the use of fuzzy logic for the design of hybrid intelligent systems based on nature-inspired optimization and their applications in areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Based on papers presented at the North American Fuzzy Information Processing Society Annual Conference (NAFIPS 2017), held in Cancun, Mexico from 16 to 18 October 2017, the book is divided into nine main parts, the first of which first addresses theoretical aspects, and proposes new concepts and algorithms based on type-1 fuzzy systems. The second part consists of papers on new...
Doubly Fed Induction Generators
Doubly Fed Induction Generators: Control for Wind Energy provides a detailed source of information on the modeling and design of controllers for the doubly fed induction generator (DFIG) used in wind energy applications. Focusing on the use of nonlinear control techniques, this book: Discusses the main features and advantages of the DFIG Describes key theoretical fundamentals and the DFIG mathematical model Develops controllers using inverse optimal control, sliding modes, and neural networks Devises an improvement to add robustness in the presence of parametric variations Details the results of real-time implementations All controllers presented in the book are tested in a laboratory prototype. Comparisons between the controllers are made by analyzing statistical measures applied to the control objectives.
Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022)
This book highlights the recent research on soft computing, pattern recognition, nature-inspired computing, and their various practical applications. It presents 69 selected papers from the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022) and 19 papers from the 14th World Congress on Nature and Biologically Inspired Computing (NaBIC 2022), which was held online, from December 14 to 16, 2022. A premier conference in the field of soft computing, artificial intelligence, and machine learning applications, SoCPaR-NaBIC 2022 brought together researchers, engineers, and practitioners whose work involves intelligent systems, network security, and their applications in industry. Including contributions by authors from over 25 countries, the book offers a valuable reference guide for all researchers, students, and practitioners in the fields of computer science and engineering.
Neural Networks Modeling and Control
Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control. As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends. - Provide in-depth analysis of neural control models and methodologies - Presents a comprehensive review of common problems in real-life neural network systems - Includes an analysis of potential applications, prototypes and future trends
Artificial Neural Networks for Engineering Applications
Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. - Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods - Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering - Contains all the theory required to use the proposed methodologies for different applications
Artificial Intelligence Innovations for Biomedical Engineering and Healthcare
Artificial Intelligence Innovations for Biomedical Engineering and Healthcare bridges the evolving domains of artificial intelligence and biomedical engineering and healthcare. In an era where data-driven insights and precision medicine are essential in healthcare, this book explores emerging trends and showcases AI's potential in transforming patient care, diagnosis, and the treatment of chronic diseases. It simplifies the relationship between artificial intelligence and biomedical engineering, elucidating how these technologies are revolutionizing self-care. The book goes on to examine how advanced technologies, including complex networks and AI-driven diagnostics are reshaping the healthc...
