This thesis is divided into two main parts. In the first part, we consider the problem of efficiently computing wavefront estimates for use in adaptive optics hardware on ground-based telescopes. Our contribution is a warm-started single-iteration multigrid algorithm that performs as well as conventional vector-matrix-multiplication methods, but at a fraction of the computational cost. We used numerical simulations to compare our algorithm to a variety of other published methods, and validated our findings at the Palomar Observatory. In the second part, we consider feedback control subject to an information constraint. Using a novel algebraic framework, we are able to prove many structural results, including a new convexity result, in a natural and purely algebraic way. We also develop a new condition we call internal quadratic invariance, under which the controller synthesis can be cast as a convex optimization problem. This describes the most general class of tractable decentralized control problems known to date. Both parts of the thesis fit into the broader question of tractability of complex systems. In the first part we look at a practical example which is difficult because of the large number of sensors and actuators. In the second part, we look at decentralized control, which is difficult because of the non-classical information constraint.

In Neurocognitive Mechanisms Gualtiero Piccinini presents the most systematic, rigorous, and comprehensive philosophical defence to date of the computational theory of cognition. His view posits that cognition involves neural computation within multilevel neurocognitive mechanisms, and includes novel ideas about ontology, functions, neural representation, neural computation, and consciousness. He begins by defending an ontologically egalitarian account of composition and realization, according to which all levels are equally real. He then explicates multiple realizability and mechanisms within this ontologically egalitarian framework, defends a goal-contribution account of teleological functions, and defends a mechanistic version of functionalism. This provides the foundation for a mechanistic account of computation, which in turn clarifies the ways in which the computational theory of cognition is a multilevel mechanistic theory supported by contemporary cognitive neuroscience. Piccinini argues that cognition is computational at least in a generic sense. He defends the computational theory of cognition from standard objections, yet also rebuts putative a priori arguments. He contends that the typical vehicles of neural computations are representations, and that, contrary to the received view, the representations posited by the computational theory of cognition are observable and manipulatable in the laboratory. He also contends that neural computations are neither digital nor analog; instead, neural computations are sui generis. He concludes by investigating the relation between computation and consciousness, suggesting that consciousness may be a functional phenomenon without being computational in nature. This book will be of interest to philosophers of cognitive science as well as neuroscientists.

An excellent introduction to feedback control system design, this book offers a theoretical approach that captures the essential issues and can be applied to a wide range of practical problems. Its explorations of recent developments in the field emphasize the relationship of new procedures to classical control theory, with a focus on single input and output systems that keeps concepts accessible to students with limited backgrounds. The text is geared toward a single-semester senior course or a graduate-level class for students of electrical engineering. The opening chapters constitute a basic treatment of feedback design. Topics include a detailed formulation of the control design program, the fundamental issue of performance/stability robustness tradeoff, and the graphical design technique of loopshaping. Subsequent chapters extend the discussion of the loopshaping technique and connect it with notions of optimality. Concluding chapters examine controller design via optimization, offering a mathematical approach that is useful for multivariable systems.

This book, dedicated to Professor Georgi M. Dimirovski on his anniversary, contains new research directions, challenges, and many relevant applications related to many aspects within the broadly perceived areas of systems and control, including signal analysis and intelligent systems. The project comprises two volumes with papers written by well known and very active researchers and practitioners. The first volume is focused on more foundational aspects related to general issues in systems science and mathematical systems, various problems in control and automation, and the use of computational and artificial intelligence in the context of systems modeling and control. The second volume is concerned with a presentation of relevant applications, notably in robotics, computer networks, telecommunication, fault detection/diagnosis, as well as in biology and medicine, and economic, financial, and social systems too.

A quick and practical introduction to the C# programming language. The text includes complete programing examples that highlight the core features of this language. In this book you will learn about: Using C# with a traditional compile run cycle, using C# within the Developer Studio environment, different data types supported in C#, control structures and input and output (i/o) in C#, key features of C# and their relationship to C, C++, Java and other programming languages.

The book includes topics, such as: path planning, avoiding obstacles, following the path, go-to-goal control, localization, and visual-based motion control. The theoretical concepts are illustrated with a developed control architecture with soft computing and artificial intelligence methods. The proposed vision-based motion control strategy involves three stages. The first stage consists of the overhead camera calibration and the configuration of the working environment. The second stage consists of a path planning strategy using several traditional path planning algorithms and proposed planning algorithm. The third stage consists of the path tracking process using previously developed Gauss and Decision Tree control approaches and the proposed Type-1 and Type-2 controllers. Two kinematic structures are utilized to acquire the input values of controllers. These are Triangle Shape-Based Controller Design, which was previously developed and Distance-Based Triangle Structure that is used for the first time in conducted experiments. Four different control algorithms, Type-1 fuzzy logic, Type-2 Fuzzy Logic, Decision Tree Control, and Gaussian Control have been used in overall system design. The developed system includes several modules that simplify characterizing the motion control of the robot and ensure that it maintains a safe distance without colliding with any obstacles on the way to the target. The topics of the book are extremely relevant in many areas of research, as well as in education in courses in computer science, electrical and mechanical engineering and in mathematics at the graduate and undergraduate levels.

This handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.