Numerous examples highlight this treatment of the use of linear quadratic Gaussian methods for control system design. It explores linear optimal control theory from an engineering viewpoint, with illustrations of practical applications. Key topics include loop-recovery techniques, frequency shaping, and controller reduction. Numerous examples and complete solutions. 1990 edition.

Optimal Control: Linear Quadratic Methods (Prentice Hall Information and System Sciences Series)

Computers & Technology

Moore, John B.

Anderson, Brian D.O.

Computer Science

PRENTICE/HALL

This work is aimed at mathematics and engineering graduate students and researchers in the areas of optimization, dynamical systems, control sys­ tems, signal processing, and linear algebra. The motivation for the results developed here arises from advanced engineering applications and the emer­ gence of highly parallel computing machines for tackling such applications. The problems solved are those of linear algebra and linear systems the­ ory, and include such topics as diagonalizing a symmetric matrix, singular value decomposition, balanced realizations, linear programming, sensitivity minimization, and eigenvalue assignment by feedback control. The tools are those, not only of linear algebra and systems theory, but also of differential geometry. The problems are solved via dynamical sys­ tems implementation, either in continuous time or discrete time , which is ideally suited to distributed parallel processing. The problems tackled are indirectly or directly concerned with dynamical systems themselves, so there is feedback in that dynamical systems are used to understand and optimize dynamical systems. One key to the new research results has been the recent discovery of rather deep existence and uniqueness results for the solution of certain matrix least squares optimization problems in geomet­ ric invariant theory. These problems, as well as many other optimization problems arising in linear algebra and systems theory, do not always admit solutions which can be found by algebraic methods.

Optimization and Dynamical Systems (COMMUNICATIONS AND CONTROL ENGINEERING)

Science & Math

Helmke, Uwe

Mathematics

Springer, Verlag

Hidden Markov Models: Estimation and Control (Stochastic Modelling and Applied Probability)

As more applications are found, interest in Hidden Markov Models continues to grow. Following comments and feedback from colleagues, students and other working with Hidden Markov Models the corrected 3rd printing of this volume contains clarifications, improvements and some new material, including results on smoothing for linear Gaussian dynamics. In Chapter 2 the derivation of the basic filters related to the Markov chain are each presented explicitly, rather than as special cases of one general filter. Furthermore, equations for smoothed estimates are given. The dynamics for the Kalman filter are derived as special cases of the authors’ general results and new expressions for a Kalman smoother are given. The Chapters on the control of Hidden Markov Chains are expanded and clarified. The revised Chapter 4 includes state estimation for discrete time Markov processes and Chapter 12 has a new section on robust control.

Hidden Markov Models: Estimation and Control (Stochastic Modelling and Applied Probability, 29)

Aggoun, Lakhdar

Elliott, Robert J.

Reference

Springer

Optimal Filtering (Dover Books on Electrical Engineering)

This graduate-level text augments and extends beyond undergraduate studies of signal processing, particularly in regard to communication systems and digital filtering theory. Vital for students in the fields of control and communications, its contents are also relevant to students in such diverse areas as statistics, economics, bioengineering, and operations research.Topics include filtering, linear systems, and estimation; the discrete-time Kalman filter; time-invariant filters; properties of Kalman filters; computational aspects; and smoothing of discrete-time signals. Additional subjects encompass applications in nonlinear filtering; innovations representations, spectral factorization, and Wiener and Levinson filtering; parameter identification and adaptive estimation; and colored noise and suboptimal reduced order filters. Each chapter concludes with references, and four appendixes contain useful supplementary material.

Networking & Cloud Computing

Dover Publications

The engineering objective of high performance control using the tools of optimal control theory, robust control theory, and adaptive control theory is more achiev able now than ever before, and the need has never been greater. Of course, when we use the term high peiformance control we are thinking of achieving this in the real world with all its complexity, uncertainty and variability. Since we do not expect to always achieve our desires, a more complete title for this book could be "Towards High Performance Control". To illustrate our task, consider as an example a disk drive tracking system for a portable computer. The better the controller performance in the presence of eccen tricity uncertainties and external disturbances, such as vibrations when operated in a moving vehicle, the more tracks can be used on the disk and the more memory it has. Many systems today are control system limited and the quest is for high performance in the real world.

High Performance Control (Systems & Control: Foundations & Applications)

Mareels, Iven

Tay, Teng-Tiow

Birkhauser

Modula-2: Text and Reference

McKay, Kenneth N.

Pascal: Text and Reference

Reston, Pub. Co

PASCAL: Text and Reference by PASCAL: by John B. Moore

Pascal, text and reference with Waterloo Pascal and Pascal VS

Hardcover BookStructured Fortran With Watfiv: Text and Reference Author: John B. Mo

Structured Fortran With Watfiv: Text and Reference

Programming Languages

See the best price to sell, buy, or rent books by Moore, John B.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Moore, John B.