Books in the Automation and Control Engineering series

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.

The book explores the behavior of networks of electric and hybrid vehicles. Topics covered include: energy management issues for aggregates of plug-in vehicles; the design of sharing systems to support electro-mobility; context awareness in the operation of electric and hybrid vehicles, and the role that this plays in a Smart City context.

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.

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.

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).

Illustrating the power, simplicity, and generality of the concept of flatness, this book explains how to identify, utilize, and apply flatness in system planning and design. It includes an assortment of exercises and models that range from elementary to complex classes of systems.

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.

"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."

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.

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.

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.

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.

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.

Provides coverage of linear, bilinear, and nonlinear optimal control algorithms for both continuous-time and discrete-time weakly coupled systems. This book presents numerous applications to real world systems from various industries, including aerospace, and discusses the design of subsystem-level optimal filters.

This book aims at information estimate methods when faults occur. It uses the model built from the plant or process, to detect and isolate failures, in contrast to traditional hardware or statistical technologies dealing with failures. It presents model-based learning and design methods for fault detection, isolation and identification.

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.

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.

Covers three major areas of control engineering (PID control, robust control, and optimal control). This book covers elegant mathematical theory and useful engineering-oriented results. It develops results relating to the design of PID and first-order controllers for continuous and discrete-time linear systems with possible delays.

This book discusses controller design in discrete time for networked control systems (NCS). The authors apply several powerful modern control techniques in discrete time to the design of intelligent controllers for such NCS. Detailed derivations, rigorous stability proofs, computer simulation examples, and downloadable MATLAB® codes are included for each case. An ideal reference for graduate students, university researchers, and practicing engineers, this book instills a solid understanding of neural network controllers and how to build them.

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.

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.

Reflects the developments in estimation theory and design techniques. This book covers the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems. It includes examples that highlight practical applications of the theory and concepts.