Presenting a unified modeling approach to demonstrate the common components inherent in all physical systems, Control Strategies for Dynamic Systems comprehensively covers the theory, design, and implementation of analog, digital, and advanced control systems for electronic, aeronautical, automotive, and industrial applications. Detailing advanced tools and strategies used to analyze controller performance, the book summarizes hardware and software utilization; frequency response and root locus methods; the evaluation of PID, phase-lag, and phase-lead controllers; and the effect of disturbances and command inputs on steady-state errors. It also includes numerous case studies and MATLAB® examples.
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For senior-level or first-year graduate-level courses in control analysis and design, and related courses within engineering, science, and management. Feedback Control of Dynamic Systems, Sixth Edition is perfect for practicing control engineers who wish to maintain their skills. This revision of a top-selling textbook on feedback control with the associated web site, FPE6e.com, provides greater instructor flexibility and student readability. Chapter 4 on A First Analysis of Feedback has been substantially rewritten to present the material in a more logical and effective manner. A new case study on biological control introduces an important new area to the students, and each chapter now includes a historical perspective to illustrate the origins of the field. As in earlier editions, the book has been updated so that solutions are based on the latest versions of MATLAB and SIMULINK. Finally, some of the more exotic topics have been moved to the web site.
This book presents Networked Control System (NCS) as a particular kind of a real-time distributed system (RTDS), composed of a set of nodes, interconnected by a network, and able to develop a complete control process. It describes important parts of the control process such as sensor and actuator activities, which rely on a real-time operating system, and a real-time communication network. As the use of common bus network architecture introduces different forms of uncertainties between sensors, actuators, and controllers, several approaches such as reconfigurable systems have been developed to tackle this problem. Moreover, modeling NCS is a challenging procedure, since there are several non-linear situations, like local saturations, uncertain time delays, dead-zones, or local situations, it is necessary to deal with. The book describes a novel strategy for modelling and control based on a fuzzy control approach and codesign strategies.
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.
Control and Dynamic Systems: Advances in Theory in Applications, Volume 30: Advances in Algorithms and Computational Techniques in Dynamic Systems Control, Part 3 of 3 discusses developments in algorithms and computational techniques for control and dynamic systems. This volume begins with the issue of decision making or optimal control in the natural environment. It then discusses large-scale systems composed of multiple sensors; algorithms for systems with multiplicative noise; stochastic differential games; Markovian targets; low-cost microcomputer and true digital control systems; and algorithms for the design of teleoperated systems. This book is an important reference for practitioners in the field who want a comprehensive source of techniques with significant applied implications.
Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way. The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints. The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs. This book addresses advanced analytical tools for characterization control, estimation and design of networked dynamic systems over fixed, probabilistic and time-varying graphs Provides coherent results on adopting a set-theoretic framework for critically examining problems of the analysis, performance and design of discrete distributed systems over graphs Deals with both homogeneous and heterogeneous systems to guarantee the generality of design results
Control and Dynamic Systems: Advances in Theory and Applications, Volume 50: Robust Control System Techniques and Applications, Part 1 of 2 is a two-volume sequence devoted to the issues and application of robust control systems techniques. This volume is composed of 10 chapters and begins with a presentation of the important techniques for dealing with conflicting design objectives in control systems. The subsequent chapters describe the robustness techniques of systems using differential-difference equations; the design of a wide class of robust nonlinear systems, the techniques for dealing with the problems resulting from the use of observers in robust systems design, and the effective techniques for the robust control on non-linear time varying of tracking control systems with uncertainties. These topics are followed by discussions of the effective techniques for the robust control on non-linear time varying of tracking control systems with uncertainties and for incorporating adaptive control techniques into a (non-adaptive) robust control design. Other chapters present techniques for achieving exponential and robust stability for a rather general class of nonlinear systems, techniques in modeling uncertain dynamics for robust control systems design, and techniques for the optimal synthesis of these systems. The last chapters provide a generalized eigenproblem solution for both singular and nonsingular system cases. These chapters also look into the stability robustness design for discrete-time systems. This book will be of value to process and systems engineers, designers, and researchers.
This book discusses analysis and design techniques for linear feedback control systems using MATLAB® software. By reducing the mathematics, increasing MATLAB working examples, and inserting short scripts and plots within the text, the authors have created a resource suitable for almost any type of user. The book begins with a summary of the properties of linear systems and addresses modeling and model reduction issues. In the subsequent chapters on analysis, the authors introduce time domain, complex plane, and frequency domain techniques. Their coverage of design includes discussions on model-based controller designs, PID controllers, and robust control designs. A unique aspect of the book is its inclusion of a chapter on fractional-order controllers, which are useful in control engineering practice.
This book is about dynamical systems that are "hybrid" in the sense that they contain both continuous and discrete state variables. Recently there has been increased research interest in the study of the interaction between discrete and continuous dynamics. The present volume provides a first attempt in book form to bring together concepts and methods dealing with hybrid systems from various areas, and to look at these from a unified perspective. The authors have chosen a mode of exposition that is largely based on illustrative examples rather than on the abstract theorem-proof format because the systematic study of hybrid systems is still in its infancy. The examples are taken from many different application areas, ranging from power converters to communication protocols and from chaos to mathematical finance. Subjects covered include the following: definition of hybrid systems; description formats; existence and uniqueness of solutions; special subclasses (variable-structure systems, complementarity systems); reachability and verification; stability and stabilizability; control design methods. The book will be of interest to scientists from a wide range of disciplines including: computer science, control theory, dynamical system theory, systems modeling and simulation, and operations research.
Analysis and Control System Techniques for Electric Power Systems, Part 1 is the first volume of a four volume sequence in this series devoted to the significant theme of ""Analysis and Control Techniques for Electric Power Systems."" The broad topics involved include transmission line and transformer modeling. Since the issues in these two fields are rather well in hand, although advances continue to be made, this four volume sequence will focus on advances in areas including power flow analysis, economic operation of power systems, generator modeling, power system stability, voltage and power control techniques, and system protection, among others. This book comprises seven chapters, with the first focusing on modern approaches to modeling and control of electric power systems. Succeeding chapters then discuss dynamic state estimation techniques for large-scale electric power systems; optimal power how algorithms; sparsity in large-scale network computation; techniques for decentralized control for interconnected systems; knowledge based systems for power system security assessment; and neural networks and their application to power engineering. This book will be of interest to practitioners in the fields of electrical and computer engineering.
