This book provides a comprehensive treatment of the principles underlying optimal constrained control and estimation. The contents progress from optimisation theory, fixed-horizon discrete optimal control, receding-horizon implementations and stability conditions to explicit solutions and numerical algorithms, moving horizon estimation, and connections between constrained estimation and control. Several case studies and further developments illustrate and expand the core principles.

Specific topics covered include:

a [ An overview of optimisation theory.

a [ Links to optimal control theory, including the discrete-minimum principle.

a [ Linear and nonlinear receding-horizon constrained control including stability.

a [ Constrained control solutions having a finite parameterisation for specific classes of problems.

a [ Numerical procedures for solving constrained optimisation problems.

a [ Output feedback optimal constrained control.

a [ Constrained state estimation.

a [ Duality between constrained estimation and control.

a [ Applications to finite alphabet control and estimation problems, cross-directional control, rudder-roll stabilisation of ships, and control over communication networks.

Constrained Control and Estimation is a self-contained treatment assuming that the reader has a basic background in systems theory, including linear control, stability and state-space methods. It is suitable for use in senior-level courses and as material for reference and self-study. A companion website is continually updated by the authors.

This book is based on a workshop entitled.: Model " Identification and Adap tive Control: From Windsurfing to Telecommunications" held in Sydney, Aus tralia, on December 16, 2000. The workshop was organized in honour of Pro fessor Brian (BDO) Anderson in recognition of his seminal contributions to systems science over the past 4 decades. . The chapters in the book have been written by colleagues, friends and stu dents of Brian Anderson. A central theme of the book is the inter relationship between identification and the use of models in real world applications. This theme has underpinned much of Brian Anderson's own contributions. The book reflects on these contributions as well as makirig important statements about possible future research directions. The subtitle of the book (From Windsurfing to Telecommunications) rec ognizes the fact that many common life experiences, such as those we en counter when learning to ride a windsurfer are models for design methods that can be used on real world advanced technological control problems. In deed, Brian Anderson extensively explored this link in his research work."

Recent developments in constrained control and estimation have created a need for this comprehensive introduction to the underlying fundamental principles. These advances have significantly broadened the realm of application of constrained control.

- Using the principal tools of prediction and optimisation, examples of how to deal with constraints are given, placing emphasis on model predictive control.

- New results combine a number of methods in a unique way, enabling you to build on your background in estimation theory, linear control, stability theory and state-space methods.

- Companion web site, continually updated by the authors.

Easy to read and at the same time containing a high level of technical detail, this self-contained, new approach to methods for constrained control in design will give you a full understanding of the subject.

Undoubtably one of the key factors influencing recent technology has been the advent of high speed computational tools. Virtually every advanced engi neering system we come in contact with these days depends upon some form of sampling and digital signal processing. Well known examples are digital tele phone systems, digital recording of audio signals and computer control. These developments have been matched by the appearance of a plethora of books which explain a variety of analysis, synthesis and design tools applica ble to sampled-data systems. The reader might therefore wonder what is distinc tive about the current book. Our observation of the existing literature is that the underlying continuous-time system is usually forgotten once the samples are tak en. The alternative point of view, adopted in this book, is to formulate the analy sis in such a way that the user is constantly reminded of the presence of the under lying continuous-time signals. We thus give emphasis to two aspects of sampled-data analysis: Firstly, we formulate the various algorithms so that the appropriate contin uous-time case is approached as the sampling rate increases. Secondly we place emphasis on the continuous-time output response rath er than simply focusing on the sampled response."