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This comprehensive book addresses 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, the text discusses the main features and advantages of the DFIG, describes key theoretical fundamentals and the DFIG mathematical model, and develops controllers using inverse optimal control, sliding modes, and neural networks. It also devises an improvement to add robustness in the presence of parametric variations, as well as details the results of real-time implementations.

This book provides a systematic framework for designing distributed controllers for multi-agent systems with general linear agent dynamics, linear agent dynamics with uncertainties, and Lipschitz nonlinear agent dynamics. The proposed consensus region decouples the design of the feedback gain matrices of the cooperative protocols from the communication graph and serves as a measure for the robustness of the protocols to variations of the communication graph. By exploiting the decoupling feature, adaptive cooperative protocols are presented that can be designed and implemented in a fully distributed fashion.

The first to address this emerging field, this book provides experts¿ cutting-edge knowledge of micro/nanotechnology, energy, and bio-systems. The editors offer an integrated view from theory to practice, covering topics ranging from sensors to energy devices and control of biology systems in cellular and molecular levels. The book also features case studies for modeling of micro/nano devices and systems, and explains how the models can be used for control and optimization. Readers benefit from learning new techniques, and applying those techniques to their own research.

This book uses numerous in-depth explanations, diagrams, calculations, and tables to provide an intensive overview of modern control theory and control system design. Mathematics are kept to a minimum, and engineering applications are stressed throughout. Completely updated and packed with student-friendly features, the sixth edition presents a range of updated examples using MATLAB®, as well as an appendix listing MATLAB functions for optimizing control system analysis and design. Over 75 percent of the problems presented in the previous edition have been revised or replaced.

Addresses the basic theory, architectures, and technologies that are necessary to implement quality of service control in wired and wireless networks. This book offers understanding of technical concepts related to computer network and wireless Internet control protocols as well as those specific to wireless ad hoc, and sensor networks.

Compares and evaluates a variety of techniques for the design, analysis, and implementation of control methodologies for systems with actuator saturation. This work presents efficient computational algorithms and control paradigms for application in the mechanical, electrical, and aerospace industries.

Focuses on the modern tactical missile, which has become a highly integrated package made up of many electronic, mechanical, electromechanical and pyrotechnic sub-systems. In addition to hardware, this title also covers the guidance algorithm and workings of the missile autopilot.

Presents modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. This book builds from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, and novel optimal control using the Hamilton-Jacobi-Bellman formulation.

This work explains how to solve industrial system problems using a novel control system design theory. This easy-to-use theory does not require designers to choose a weighting function and enables the controllers to be designed or tuned for quantitative engineering performance indices such as overshoot. Equally emphasizing theoretical and application aspects of the subject, the book bridges classical control theory and the newly arriving generation of robust control theory. It includes numerous exercises and examples drawn from aeronautical, mechanical, and chemical engineering.

This reference uses linear systems theory and matrix operations to offer practical tool sets for intelligent diagnosis and prognosis in industrial networked systems. Giving an overview of diagnosis and prognosis, the book covers fundamental concepts of vectors, matrices, and linear systems. It develops mathematical machineries and decision software tools for real-world applications, including modal parametric identification (MPI) and probabilistic small-signal stability assessment. It also discusses future directions for intelligent diagnosis and prognosis. Written in a concise and accessible style, the book supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students.

Using real-life examples to illustrate the performance of learning algorithms and instructing readers how to apply them to practical applications, this work offers a comprehensive treatment of subspace learning algorithms for neural networks. It summarizes a decade of high quality research offering a host of practical applications.

Fuzzy logic control (FLC) has proven to be a popular control methodology for many complex systems in industry. This book is devoted to the systematic analysis and synthesis of model-based fuzzy control systems. It fully explains the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy systems.

Dealing with a method of fault tolerant control, this title presents a theoretical framework for reliable control in linear systems with adaptive mechanisms. It also presents guidelines for designing control systems with guaranteed stability and desired performance in the presence of actuator/sensor failures.

From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. This title provides a comprehensive exploration of the field of Dynamic Programming (DP) and Reinforcement Learning (RL).

Helps to explore the challenges presented by modern hard disk drives and learn how to overcome them. This book presents an overview of history, components, operating principles, and industry trends, and examines the design and manufacturing challenges. It compares various design approaches for both single- and dual-stage servomechanisms.

From the ox carts and pottery wheels of ancient times to the spacecrafts and disk drives of today, efficiency and quality has always been dependent on the engineer's ability to anticipate and control the effects of vibration. This title answers the essential needs of practitioners in systems and control.

Presents systematic methods for achieving stable, agile, and efficient locomotion in bipedal machines. This book describes dynamic locomotion in planar bipedal robots, from both theoretical and practical points of view. It is suitable for researchers and practitioners seeking to move beyond the quasi-static walking of powered bipedal robots.

Sliding Mode Control (SMC) is a universal design tool for the robust control of linear and nonlinear systems. This book explains the conventional SMC methodology while examining different design principles. It also includes chapters on automotive applications, chattering suppression, and control of power converters.

Presents nonlinear control algorithms for a benchmark mechanical system actuated by different types of electric machinery. This work emphasizes system stability and robustness - pivotal in the development of optimal position trajectory controllers for common motors.

Provides various theories and methodologies for implementing cost and time-saving improvements to contemporary manufacturing systems. This text supplies simple and complex industrial manufacturing system examples to illustrate different concepts, theories, and approaches for solving real-life application problems.

Offering an introduction to the field of soft computing techniques, this book covers various major techniques in artificial intelligence. It highlights research and applications, addresses issues encountered in the development of applied systems, and describes a range of intelligent systems techniques.

"Illustrates the analysis, behavior, and design of linear control systems using classical, modern, and advanced control techniques. Covers recent methods in system identification and optimal, digital, adaptive, robust, and fuzzy control, as well as stability, controllability, observability, pole placement, state observers, input-output decoupling, and model matching."

Offers a survey of control systems for serial-link robot arms and acknowledges how robotic device performance hinges upon a well-developed control system. This book explicates theoretical and mathematical requisites for controls design and summarizes techniques in computer simulation and implementation of controllers.

Reflecting the authors' experience in fuzzy control, this book describes the basic concepts for solving a great number of practical control problems. It focuses on hybrid, adaptive, and self-learning fuzzy control schemes that have proved to be superior in solving demanding nonlinear control problems.

Provides systematic design approaches for the identification, control, and recognition of nonlinear systems in uncertain environments. This book introduces the concepts of deterministic learning theory and then discusses the persistent excitation property of RBF networks.