This book provides an update of the latest research in control of time delay systems and applications by world leading experts. It will appeal to engineers, researchers and students in Control.

In view of the rapid changes in requirements, it has became necessary to place at the reader's disposal a book dealing with basic and advanced concepts and techniques for the monitoring and control of chemical and biochemical processes, as well as with the aspects of the implementation of these different robust techniques. To make the ideas covered in this book accessible to a larger audience, the authors attempted to present a balanced view of the theoretical and practical issues of control systems. Different cases are presented to illustrate the controller and observer design procedures...

The purpose of this fantastically useful book is to lay out an overview on possible tools for state reconstruction in nonlinear systems. Here, basic observability notions and observer structures are recalled, together with ingredients for advanced designs on this basis. The problem of state reconstruction in dynamical systems, known as observer problem, is crucial for controlling or even merely monitoring processes. For linear systems, the theory has been well established for several years, so this book attempts to tackle the problem for non-linear systems.

This book employs the powerful and popular adaptive backstepping control technology to design controllers for dynamic uncertain systems with non-smooth nonlinearities. Various cases including systems with time-varying parameters, multi-inputs and multi-outputs, backlash, dead-zone, hysteresis and saturation are considered in design and analysis. For multi-inputs and multi-outputs systems, both centralized and decentralized controls are addressed.

This book not only presents recent research results including theoretical success and practical development such as the proof of system...

This volume contains a collection of papers in control theory and applications presented at a conference in honor of Clyde Martin on the occasion of his 60th birthday, held in Lubbock, Texas, November 14-15, 2003.

Control and estimation of linear systems with state-multiplicative noise in the H-infinity setting is covered in this monograph. Multiplicative noise appears in systems where the process or measurement noise levels depend on the system state vector. Such systems are relevant when a gain-scheduled controller utilizes a noisy gain-scheduling parameter or when the noise level depends on one or more of the states; the latter is encountered, for example, in radar measurements where larger ranges involve higher noise level. The last decade has witnessed a resurgence of interest in the...

Advanced Topics in Control Systems Theory contains selected contributions written by lecturers at the second (annual) Formation d'Automatique de Paris (FAP) (Graduate Control School in Paris). It is addressed to graduate students and researchers in control theory with topics touching on a variety of areas of interest to the control community such as cascaded systems, flatness, optimal control, and Hamiltonian and infinite-dimensional systems. The reader is provided with a well-integrated synthesis of the latest thinking in these subjects without the need for an exhaustive...

The authors present a study of the H-infinity control problem and related topics for descriptor systems, described by a set of nonlinear differential-algebraic equations. They derive necessary and sufficient conditions for the existence of a controller solving the standard nonlinear H-infinity control problem considering both state feedback and output feedback. One such condition for the output feedback control problem to be solvable is obtained in terms of two Hamilton-Jacobi inequalities and a weak coupling condition; a parameterization of a family of output feedback controllers solving...

Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show.

In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents...