This book covers systematically and in a simple language the mathematical and physical foundations of controlling deterministic and stochastic evolutionary processes in systems with a high degree of complexity. Strong emphasis is placed on concepts, methods and techniques for modelling, assessment and the solution or estimation of control problems in an attempt to understand the large variability of these problems in several branches of physics, chemistry and biology as well as in technology and economics. The main focus of the book is on a clear physical and mathematical understanding of the dynamics and kinetics behind several kinds of control problems and their relation to self-organizing principles in complex systems. The book is a modern introduction and a helpful tool for researchers, engineers as well as post-docs and graduate students interested in an application oriented control theory and related topics.

Bridging the basics to recent research advances, this is the ideal learning and reference work for physicists studying control theory.

Control theory, an interdisciplinary concept dealing with the behaviour of dynamical systems, is an important but often overlooked aspect of physics. This is the first broad and complete treatment of the topic tailored for physicists, one which goes from the basics right through to the most recent advances. Simple examples develop a deep understanding and intuition for the systematic principles of control theory, beyond the recipes given in standard engineering-focused texts. Up-to-date coverage of control of networks and complex systems, and a thorough discussion of the fundamental limits of control, including the limitations placed by causality, information theory, and thermodynamics are included. In addition it explores important recent advances in stochastic thermodynamics on the thermodynamic costs of information processing and control. For all students of physics interested in control theory, this classroom-tested, comprehensive approach to the topic with online solutions and further materials delivers both fundamental principles and current developments.

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

Control Theory is a field of applied mathematics and engineering that deals with the basic principles underlying the analysis and design of control systems. "Controlling a system" means to influence the behavior of the system in order to achieve a desired goal. Control theory deals with the use of a controller to achieve this purpose. Control theory has been recognized as a mathematical subject since the 1960's; it has contributed to scientific and technological progress in many areas over the last few decades. Control theory has been extensively used in modern society, from simple applications such as temperature devices to sophisticated systems in space flight. The aim of this book is to solve different problems concerning control systems. This book joins a number of recent works in control theory and is useful as a source for researchers in this field concerning control systems.

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Physics of Biological Action and Perception helps researchers interested in exploring biological motor control from a physics or alternative viewpoint perspective. The book introduces the idea of parametric control as a distinguishing feature of living systems. Sections cover how the CNS creates stable percepts based on fuzzy and continuously changing signals from numerous receptors and the variable processes related to ongoing actions. The author also develops the idea of control with referent coordinates to stability of salient variables in fields typically united under the label of "cognition." Examples of this include communication (how the gist of a message is preserved despite variability of phrases), thought processes (how one can solve a mental problem via different logical routes), and playing chess (how one selects an optimal move given a position on the board). The book is written for researchers, instructors, clinicians and other professionals in all the fields related to biological movement and perception. - Presents a unifying theory of motor control based on physics - Encompasses action, perception and cognition - Discusses referent coordinates, kinesthetic perception and stability of actions - Identifies the importance of the CNS over computational brain function

The essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory

A survey of how engineering techniques from control and systems theory can be used to help biologists understand the behavior of cellular systems.

Geared primarily to an audience consisting of mathematically advanced undergraduate or beginning graduate students, this text may additionally be used by engineering students interested in a rigorous, proof-oriented systems course that goes beyond the classical frequency-domain material and more applied courses. The minimal mathematical background required is a working knowledge of linear algebra and differential equations. The book covers what constitutes the common core of control theory and is unique in its emphasis on foundational aspects. While covering a wide range of topics written in a standard theorem/proof style, it also develops the necessary techniques from scratch. In this second edition, new chapters and sections have been added, dealing with time optimal control of linear systems, variational and numerical approaches to nonlinear control, nonlinear controllability via Lie-algebraic methods, and controllability of recurrent nets and of linear systems with bounded controls.