Control Theory Applications for Dynamic Production Systems Apply the fundamental tools of linear control theory to model, analyze, design, and understand the behavior of dynamic production systems In Control Theory Applications for Dynamic Production Systems: Time and Frequency Methods for Analysis and Design, distinguished manufacturing engineer Dr. Neil A. Duffie delivers a comprehensive explanation of how core concepts of control theorical analysis and design can be applied to production systems. Time-based perspectives on response to turbulence are augmented by frequency-based perspectives, fostering new understanding and guiding design of decision-making. The time delays intrinsic to decision making and decision implementation in production systems are addressed throughout. Readers will discover methods for calculating time response and frequency response, modeling using transfer functions, assessing stability, and design of decision making for closed-loop production systems. The author has included real-world examples emphasizing the different components of production systems and illustrating how practical results can be quickly obtained using straightforward Matlab programs (which can easily be translated to other platforms). Avoiding unnecessary theoretical jargon, this book fosters an in-depth understanding of key tools of control system engineering. It offers: A thorough introduction to core control theoretical concepts of analysis and design of dynamic production systems Comprehensive and integrated explorations of continuous-time and discrete-time models of production systems, employing transfer functions and block diagrams Practical discussions of time response, frequency response, fundamental dynamic behavior, closed-loop production systems, and the design of decision-making In-depth examples of the analysis and design of complex dynamic behavior requiring approaches such as matrices of transfer functions and modeling of multiple sampling rates Perfect for production, manufacturing, industrial, and control system engineers, Control Theory Applications for Dynamic Production Systems will also earn a place in the libraries of students taking advanced courses on industrial system digitalization, dynamics, and design.

Control Theory Applications for Dynamic Production Systems Apply the fundamental tools of linear control theory to model, analyze, design, and understand the behavior of dynamic production systems In Control Theory Applications for Dynamic Production Systems: Time and Frequency Methods for Analysis and Design, distinguished manufacturing engineer Dr. Neil A. Duffie delivers a comprehensive explanation of how core concepts of control theorical analysis and design can be applied to production systems. Time-based perspectives on response to turbulence are augmented by frequency-based perspectives, fostering new understanding and guiding design of decision-making. The time delays intrinsic to decision making and decision implementation in production systems are addressed throughout. Readers will discover methods for calculating time response and frequency response, modeling using transfer functions, assessing stability, and design of decision making for closed-loop production systems. The author has included real-world examples emphasizing the different components of production systems and illustrating how practical results can be quickly obtained using straightforward Matlab programs (which can easily be translated to other platforms). Avoiding unnecessary theoretical jargon, this book fosters an in-depth understanding of key tools of control system engineering. It offers: A thorough introduction to core control theoretical concepts of analysis and design of dynamic production systems Comprehensive and integrated explorations of continuous-time and discrete-time models of production systems, employing transfer functions and block diagrams Practical discussions of time response, frequency response, fundamental dynamic behavior, closed-loop production systems, and the design of decision-making In-depth examples of the analysis and design of complex dynamic behavior requiring approaches such as matrices of transfer functions and modeling of multiple sampling rates Perfect for production, manufacturing, industrial, and control system engineers, Control Theory Applications for Dynamic Production Systems will also earn a place in the libraries of students taking advanced courses on industrial system digitalization, dynamics, and design.

In recent years, a considerable amount of effort has been devoted, both in industry and academia, towards the development of advanced methods of control theory with focus on its practical implementation in various fields of human activity such as space control, robotics, control applications in marine systems, control processes in agriculture and food production.Control Systems: Theory and Applications consists of selected best papers which were presented at XXIV International conference on automatic control “Automatics 2017” (September 13-15, 2017, Kyiv, Ukraine) organized by Ukrainian Association on Automatic Control (National member organization of IFAC – International Federation on Automatic Control) and National University of Life and Environmental Sciences of Ukraine. More than 120 presentations where discussed at the conference, with participation of the scientists from the numerous countries. The book is divided into two main parts, a first on Theory of Automatic Control (5 chapters) and the second on Control Systems Applications (8 chapters). The selected chapters provide an overview of challenges in the area of control systems design, modeling, engineering and implementation and the approaches and techniques that relevant research groups within this area are employing to try to resolve these.This book on advanced methods of control theory and successful cases in the practical implementation is ideal for personnel in modern technological processes automation and SCADA systems, robotics, space and marine industries as well as academic staff and master/research students in computerized control systems, automatized and computer-integrated systems, electrical and mechanical engineering.

Optimal control methods are used to determine optimal ways to control a dynamic system. The theoretical work in this field serves as a foundation for the book, which the authors have applied to business management problems developed from their research and classroom instruction. Sethi and Thompson have provided management science and economics communities with a thoroughly revised edition of their classic text on Optimal Control Theory. The new edition has been completely refined with careful attention to the text and graphic material presentation. Chapters cover a range of topics including finance, production and inventory problems, marketing problems, machine maintenance and replacement, problems of optimal consumption of natural resources, and applications of control theory to economics. The book contains new results that were not available when the first edition was published, as well as an expansion of the material on stochastic optimal control theory.

This edited volume contains 16 research articles. It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the book is highly multi-disciplinary. The book is dedicated to Professor Suresh Sethi on the occasion of his 60th birthday, in view of his distinguished career.

This open access Brief introduces the basic principles of control theory in a concise self-study guide. It complements the classic texts by emphasizing the simple conceptual unity of the subject. A novice can quickly see how and why the different parts fit together. The concepts build slowly and naturally one after another, until the reader soon has a view of the whole. Each concept is illustrated by detailed examples and graphics. The full software code for each example is available, providing the basis for experimenting with various assumptions, learning how to write programs for control analysis, and setting the stage for future research projects. The topics focus on robustness, design trade-offs, and optimality. Most of the book develops classical linear theory. The last part of the book considers robustness with respect to nonlinearity and explicitly nonlinear extensions, as well as advanced topics such as adaptive control and model predictive control. New students, as well as scientists from other backgrounds who want a concise and easy-to-grasp coverage of control theory, will benefit from the emphasis on concepts and broad understanding of the various approaches. Electronic codes for this title can be downloaded from https://extras.springer.com/?query=978-3-319-91707-8