Bücher der Reihe Automation and Control Engineering

"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."

The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple outputs. It provides solutions for the output trajectory tracking problem of unknown nonlinear systems based on sliding modes and inverse optimal control scheme.

Modeling fuzzy control has been a very active research and application area in control engineering. However, there are few books available that cover the area in any depth. Written by a well-known expert who has published more than 100 papers in top international journals, this book gives insight into the latest approaches for the analysis and synthesis of fuzzy systems. It systematically presents design techniques applied to the Takagi¿Sugeno class of fuzzy controllers widely used in successful practical applications. The book covers issues of robustness, stability, and conformity along with other state-of-the-art control techniques, such as model predictive control.

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.

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 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.

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 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.

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 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.

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 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.

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.

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.