This book provides a comprehensive treatment of the nonlinear output regulation problem. It contains up-to-date research results and algorithms and tools for approaching and solving this and other related problems. Output regulation is a general mathematical formulation of many control problems encountered in daily life, including cruise control of automobiles, landing and takeoff of aircraft, manipulation of robot arms, orbiting of satellites, and speed regulation of motors. In addition to the previously obtained results on the output regulation problem is the newly developed general framework that converts the robust output regulation problem for a given nonlinear system into a robust stabilization problem for an augmented system. This general framework is based on the construction of nonlinear internal models and offers greater flexibility to incorporate recent new stabilization techniques, thus setting the stage for systematically tackling robust output regulation with global stability.

Nonlinear Output Regulation: Theory and Applications (Advances in Design and Control, Series Number 8)

Computers & Technology

HUANG, JIE

Computer Science

SIAM: Society for Industrial and Applied Mathematics

Nonlinear Dynamics and Vibration Control of Flexible Systems

Science & Math

Physics

CRC-Press

Nonlinear H2/H-Infinity Constrained Feedback Control: A Practical Design Approach Using Neural Networks (Advances in Industrial Control)

This book provides techniques to produce robust, stable and useable solutions to problems of H-infinity and H2 control in high-performance, non-linear systems for the first time. The book is of importance to control designers working in a variety of industrial systems. Case studies are given and the design of nonlinear control systems of the same caliber as those obtained in recent years using linear optimal and bounded-norm designs is explained.

Abu-Khalaf, Murad

Lewis, Frank L.

Certification

Springer

Cooperative Control of Multi-agent Systems: Distributed-Observer and Distributed-Internal-Model Approaches (Advances in Industrial Control)

Cai, He

Su, Youfeng

Reference

The main focus of this book is a pair of cooperative control problems: consensus and cooperative output regulation. Its emphasis is on complex multi-agent systems characterized by strong nonlinearity, large uncertainty, heterogeneity, external disturbances and jointly connected switching communication topologies. The cooperative output regulation problem is a generalization of the classical output regulation problem to multi-agent systems and it offers a general framework for handling a variety of cooperative control problems such as consensus, formation, tracking and disturbance rejection. &nbsp; The book strikes a balance between rigorous mathematical proof and engineering practicality. Every design method is systematically presented together with illustrative examples and all the designs are validated by computer simulation. The methods presented are applied to several practical problems, among them the leader-following consensus problem of multiple Euler-Lagrangesystems, attitude synchronization of multiple rigid-body systems, and power regulation of microgrids. The book gives a detailed exposition of two approaches to the design of distributed control laws for complex multi-agent systems--the distributed-observer and distributed-internal-model approaches. Mastering both will enhance a reader's ability to deal with a variety of complex real-world problems. &nbsp; Cooperative Control of Multi-agent&nbsp;Systems&nbsp;can be used as a textbook for graduate students in engineering, sciences, and mathematics, and can also serve as a reference book for practitioners and theorists in both industry and academia. Some knowledge of the fundamentals of linear algebra, calculus, and linear systems are needed to gain maximum benefit from this book. &nbsp; Advances in Industrial Control&nbsp;reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

The core of this textbook is a systematic and self-contained treatment of the nonlinear stabilization and output regulation problems. Its coverage embraces both fundamental concepts and advanced research outcomes and includes many numerical and practical examples. Several classes of important uncertain nonlinear systems are discussed. The state-of-the art solution presented uses robust and adaptive control design ideas in an integrated approach which demonstrates connections between global stabilization and global output regulation allowing both to be treated as stabilization problems.
Stabilization and Regulation of Nonlinear Systems takes advantage of rich new results to give students up-to-date instruction in the central design problems of nonlinear control, problems which are a driving force behind the furtherance of modern control theory and its application. The diversity of systems in which stabilization and output regulation become significant concerns in the mathematical formulation of practical control solutions―whether in disturbance rejection in flying vehicles or synchronization of Lorenz systems with harmonic systems―makes the text relevant to readers from a wide variety of backgrounds. Many exercises are provided to facilitate study and solutions are freely available to instructors via a download from springerextras.com.
Striking a balance between rigorous mathematical treatment and engineering practicality, Stabilization and Regulation of Nonlinear Systems is an ideal text for graduate students from many engineering and applied-mathematical disciplines seeking a contemporary course in nonlinear control. Practitioners and academic theorists will also find this book a useful reference on recent thinking in this field.

Stabilization and Regulation of Nonlinear Systems: A Robust and Adaptive Approach (Advanced Textbooks in Control and Signal Processing)

Chen, Zhiyong

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