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Low Rank Approximation
Data Approximation by Low-complexity Models details the theory, algorithms, and applications of structured low-rank approximation. Efficient local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. Much of the text is devoted to describing the applications of the theory including: system and control theory; signal processing; computer algebra for approximate factorization and common divisor computation; computer vision for image deblurring and segmentation; machine learning for information retrieval and clustering; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; and psychometrics for factor analysis. Software implementation of the methods is given, making the theory directly applicable in practice. All numerical examples are included in demonstration files giving hands-on experience and exercises and MATLAB® examples assist in the assimilation of the theory.
Nanostructured Materials and Nanotechnology, Volume 28, Issue 6
Papers from The American Ceramic Society's 31st International Conference on Advanced Ceramics and Composites, held in Daytona Beach, Florida, January 21-26, 2007. Topics include synthesis, fictionalization, processing, and characterization of nanomaterials; structure-property correlations at nanometer length scales; bio- and magnetic nanomaterials; fundamentals in nanoscale systems and processes; nanostructured materials for chemical mechanical planarization, display, health and cosmetic applications; nanotubes and nanowires, nanolithography, and industrial development of nanomaterials.
Modeling, Design, and Optimization of Net-Zero Energy Buildings
Building energy design is currently going through a period of major changes. One key factor of this is the adoption of net-zero energy as a long term goal for new buildings in most developed countries. To achieve this goal a lot of research is needed to accumulate knowledge and to utilize it in practical applications. In this book, accomplished international experts present advanced modeling techniques as well as in-depth case studies in order to aid designers in optimally using simulation tools for net-zero energy building design. The strategies and technologies discussed in this book are, however, also applicable for the design of energy-plus buildings. This book was facilitated by Interna...
Flow Control by Feedback
This accessible book pioneers feedback concepts for control mixing. It reviews research results appearing over the last decade, and contains control designs for stabilization of channel, pipe and bluff body flows, as well as control designs for the opposite problem of mixing enhancement.
Periodic Systems
Periodic Systems gives a comprehensive treatment of the theory of periodic systems, including the problems of filtering and control. Topics covered include: basic issues, including Floquet theory, controllability and observability, canonical decomposition, system norms and Lyapunov and robust stability; the problem of state estimation in its various forms, filtering, prediction and smoothing; control design methods, particularly optimal and robust control. The text focuses on discrete-time signals and systems; however, an overview of the entire field, including the continuous-time case, is provided in the first chapter. The authors’ presentation of the theory and results is mathematically rigorous while maintaining a readable style, avoiding excessive formalism. This makes the book accessible to graduate students and researchers from the fields of engineering, physics, economics and mathematics.
Positive 1D and 2D Systems
This text is devoted to the positive multivariable 1D and 2D linear, time-invariant, finite-dimensional system. The book is based on the author's lectures for Ph.D. students, delivered at Warsaw University of Technology in the academic year 1999/2000. The book consists of two parts; the first part is devoted to the 1D positive linear systems and the second to the 2D positive linear systems described by the Rosser model and the Fornasini-Marchesini models. Definitions, basic properties and theorems concerning positive matrices and graphs are presented; the externally and internally positive linear continuous-time and discrete-time linear systems are considered; and the reachability, controlability and observability of positive linear systems are discussed. The realisation problem for positive 1D and 2D systems is also considered, and the 2D models of externally and internally positive and their properties and controllability and minimum energy control of positive 2D systems are investigated.
Differential Neural Networks for Robust Nonlinear Control
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.).
Stability Theory of Switched Dynamical Systems
There are plenty of challenging and interesting problems open for investigation in the field of switched systems. Stability issues help to generate many complex nonlinear dynamic behaviors within switched systems. The authors present a thorough investigation of stability effects on three broad classes of switching mechanism: arbitrary switching where stability represents robustness to unpredictable and undesirable perturbation, constrained switching, including random (within a known stochastic distribution), dwell-time (with a known minimum duration for each subsystem) and autonomously-generated (with a pre-assigned mechanism) switching; and designed switching in which a measurable and freely-assigned switching mechanism contributes to stability by acting as a control input. For each of these classes this book propounds: detailed stability analysis and/or design, related robustness and performance issues, connections to other control problems and many motivating and illustrative examples.
Analysis and Decision Making in Uncertain Systems
A unified and systematic description of analysis and decision problems within a wide class of uncertain systems, described by traditional mathematical methods and by relational knowledge representations. Prof. Bubnicki takes a unique approach to stability and stabilization of uncertain systems.
Dissipative Systems Analysis and Control
This book deals with the analysis and feedback control of dissipative dynamical systems. It presents the background of dissipative systems theory. Linear as well as nonlinear systems are treated, and many examples are given throughout the chapters. Some infinite dimensional and non-smooth examples are also included. The emphasis is put on the application towards the design of stable feedback control laws. Then the theory is illustrated on physical examples; (Lagrangian and Hamiltonian systems are thoroughly studied, as well as adaptive control). It is shown how the dissipativity properties of a system can be used in the design of stable feedback controllers. Some experimental results are presented which corroborate the theoretical developments. This monograph is primarily for readers who wish to get aquainted with Dissipative Systems Theory, and its uses in Systems and Control and Robotics. It constitutes an advanced introduction to the topic, and is the first volume ever published which is dedicated entirely to this subject.
