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Some robots perform autonomously, and some are controlled remotely. This book discusses the different ways you can send signals to your robot and how to set up circuit boards. There are also examples of the ways geometry, algebra, and trigonometry are used to program a robot to follow a designated path.
Some robots perform autonomously, and some are controlled remotely. This book discusses the different ways you can send signals to your robot and how to set up circuit boards. There are also examples of the ways geometry, algebra, and trigonometry are used to program a robot to follow a designated path.
In a mathematical programming problem, an optimum (maxi mum or minimum) of a function is sought, subject to con straints on the values of the variables. In the quarter century since G. B. Dantzig introduced the simplex method for linear programming, many real-world problems have been modelled in mathematical programming terms. Such problems often arise in economic planning - such as scheduling industrial production or transportation - but various other problems, such as the optimal control of an interplanetary rocket, are of similar kind. Often the problems involve nonlinear func tions, and so need methods more general than linear pro gramming. This book presents a unified theory of nonlinear mathe matical programming. The same methods and concepts apply equally to 'nonlinear programming' problems with a finite number of variables, and to 'optimal control' problems with e. g. a continuous curve (i. e. infinitely many variables). The underlying ideas of vector space, convex cone, and separating hyperplane are the same, whether the dimension is finite or infinite; and infinite dimension makes very little difference to the proofs. Duality theory - the various nonlinear generaliz ations of the well-known duality theorem of linear program ming - is found relevant also to optimal control, and the , PREFACE Pontryagin theory for optimal control also illuminates finite dimensional problems. The theory is simplified, and its applicability extended, by using the geometric concept of convex cones, in place of coordinate inequalities.
Author : Michael D. Canon Publisher : New York ; Toronto : McGraw-Hill Book Company Page : 310 pages File Size : 50,88 MB Release : 1970 Category : Control theory ISBN :
"This book has three basic aims: to present a unified theory of optimization, to introduce nonlinear programming algorithms to the control engineer, and to introduce the nonlinear programming expert to optimal control. This volume can be used either as a graduate text or as a reference text." --Preface.
Do big math on small machines Write fast and accurate library functions Master analytical and numerical calculus Perform numerical integration to any order Implement z-transform formulas Need to learn the ins and outs of the fundamental math functions in
The 3rd edition strikes a nice balance between mathematical rigor and engineering oriented applications, helping students to understand the mathematical and engineering aspects of control theory.The book makes effective use of the tools provided by MATLAB® (and includes material about using the tools provided by the Python® programming language) in the design and analysis of control systems without allowing the computer-based tools to substitute for knowledge of control theory. The examples in the text are carefully designed to develop the student's intuition — in both mathematics and engineering.With over 90 solved homework problems and about 200 figures, this invaluable title will benefit junior and senior level university students in engineering.
This book is primarily a research monograph that presents in a unified man ner some recent research on a class of hybrid dynamical systems (HDS). The book is intended both for researchers and advanced postgraduate stu dents working in the areas of control engineering, theoretical computer science, or applied mathematics and with an interest in the emerging field of hybrid dynamical systems. The book assumes competence in the basic mathematical techniques of modern control theory. The material presented in this book derives from a period of fruitful research collaboration between the authors that began in 1994 and is still ongoing. Some of the material contained herein has appeared as isolated results in journal papers and conference proceedings. This work presents this material in an integrated and coherent manner and also presents many new results. Much of the material arose from joint work with students and colleagues, and the authors wish to acknowledge the major contributions made by Ian Petersen, Efstratios Skafidas, Valery Ugrinovskii, David Cook, Iven Mareels, and Bill Moran. There is currently no precise definition of a hybrid dynamical system; however, in broad terms it is a dynamical system that involves a mixture of discrete-valued and continuous-valued variables. Since the early 1990s, a bewildering array of results have appeared under the umbrella of HDS, ranging from the analysis of elementary on-off control systems to sophis ticated mathematical logic-based descriptions of large real-time software systems.
A Programmer's Introduction to Mathematics uses your familiarity with ideas from programming and software to teach mathematics. You'll learn about the central objects and theorems of mathematics, including graphs, calculus, linear algebra, eigenvalues, optimization, and more. You'll also be immersed in the often unspoken cultural attitudes of mathematics, learning both how to read and write proofs while understanding why mathematics is the way it is. Between each technical chapter is an essay describing a different aspect of mathematical culture, and discussions of the insights and meta-insights that constitute mathematical intuition. As you learn, we'll use new mathematical ideas to create wondrous programs, from cryptographic schemes to neural networks to hyperbolic tessellations. Each chapter also contains a set of exercises that have you actively explore mathematical topics on your own. In short, this book will teach you to engage with mathematics. A Programmer's Introduction to Mathematics is written by Jeremy Kun, who has been writing about math and programming for 10 years on his blog "Math Intersect Programming." As of 2020, he works in datacenter optimization at Google.The second edition includes revisions to most chapters, some reorganized content and rewritten proofs, and the addition of three appendices.