Dimensional analysis is an engineering tool that is widely applied to numerous engineering problems, but has only recently been applied to control theory and problems such as identification and model reduction, robust control, adaptive control, and PID control.
Application of Dimensional Analysis in Systems Modeling and Control Design provides an introduction to the fundamentals of dimensional analysis for control engineers, and shows how they can exploit the benefits of the technique to theoretical and practical control problems. Topics covered include dimensional analysis and dimensional similarity, dynamical systems dimensionless representation, dimensionless systems identification and model order reduction, homogeneity of PID tuning rules, dimensionless PID tuning rules comparison, dimensional analysis control fundamentals, control of dimensionally similar systems, and adaptive control in the presence of input saturation.
Applied Control Theory
J.R. Leigh The Institution of Engineering and Technology, 1987 Library of Congress TJ213.L334 1987 | Dewey Decimal 629.8
'To the surprise of some undergraduates, processes do not carry labels marking their variables nor, alas, are they conveniently classified into linear, nonlinear, stochastic, etc., categories. The ability to come to terms with this situation is a prerequisite for anyone proposing to succeed in an industrial environment.' This quotation from Chapter 1 characterises the viewpoint of the book, which is concerned with the application of control theory to real problems in their industrial context.
The book is structured around the following beliefs:
(a) Economic aspects must be considered at an early stage of any project.
(b) Simple techniques and ready-made manufacturer's solutions should be applied wherever possible.
(c) More advanced techniques will be received enthusiastically in those applications where they can offer a genuine contribution.
(d) Control systems using distributed microprocessor power will have an impact that is difficult to exaggerate. Control engineers must become familiar with the concepts involved.
(e) Familiarity with a wide range of applications is indispensable in developing an efficient approach in the field of applied control theory.
This second edition includes new material and supporting references on:
programmable logic controllers
distributed computer control systems
The book should be accessible to a wide variety of engineers. Preferably they should have an elementary knowledge of automatic control theory.
This book collects together in one volume a number of control engineering solutions, intended to be representative of solutions applicable to a broad class of control problems, and outlines possible alternative approaches to finding them. This is neither a control theory book nor a handbook of laboratory experiments, although it includes both the basic theory of control and practical laboratory set-ups to illustrate the solutions proposed.
A number of control problems are identified and discussed, from the initial phase of experimental construction of a model of the process to the final steps of hardware and software implementation, for several illustrative applications including a motor drive and a small scale robot. PID tuning and anti-wind-up, disturbance rejection, time delays and distributed systems, state feedback and observer design, multiloop interaction, fault detection and supervision, and fuzzy logic control are some of the control issues treated.
Written by a team of European experts, the book should interest a broad audience. Control engineering students will find potential applications for control theory and workable examples of practical control problems. Most of the laboratory set-ups will be easy to replicate by control engineering teaching staff, enabling practical activity to complement theoretical and exercise class sessions. Applied control engineers will find guidelines to approach the solution of their own control problems, including discussion of alternative methods and results to be expected. The publication of this book represents the final outcome of a European TEMPUS project to improve educational practice in automation and control technology.
J.R. Leigh The Institution of Engineering and Technology, 2004 Library of Congress TJ213.L335 2004 | Dewey Decimal 629.8312
Concise highly readable book emphasising the concepts and principles that are prerequisite for understanding both traditional and recent control theory.
The text is enlivened by a large number of interesting interludes that complement the main text.
This second edition of Control Theory: A Guided Tour (IEE 1992) has been fully revised and enlarged and now contains an introduction to H infinity methods as well as a new chapter on Artificial Intellingence (AI) methods and a retrospective review of how control theory developed. All the topics covered can be taken further using the extensive annotated reference section.
Using clear tutorial examples, this fully updated new edition concentrates on explaining and illustrating the concepts that are at the heart of control theory.
It seeks to develop a robust understanding of the underlying principles around which the control subject is built. This simple framework is studded with references to more detailed treatments and also has interludes that are intended to inform and entertain.
The book is intended as a companion on the journey through control theory and although the early chapters concentrate on fundamental ideas such as feedback and stability, later chapters deal with more advanced topics such as state variables, optimisation, estimation, Kalman filtering and robust control.
This comprehensive book covers the state-of-the-art in control-oriented modelling and identification techniques. With contributions from leading researchers in the subject, Control-oriented Modelling and Identification: Theory and practice covers the main methods and tools available to develop advanced mathematical models suitable for control system design, including: object-oriented modelling and simulation; projection-based model reduction techniques; integrated modelling and parameter estimation; identification for robust control of complex systems; subspace-based multi-step predictors for predictive control; closed-loop subspace predictive control; structured nonlinear system identification; and linear fractional LPV model identification from local experiments using an H1-based glocal approach.
This book also takes a practical look at a variety of applications of advanced modelling and identification techniques covering spacecraft dynamics, vibration control, rotorcrafts, models of anaerobic digestion, a brake-by-wire racing motorcycle actuator, and robotic arms.
Robust control theory allows for changes in a system whilst maintaining stability and performance. Applications of this technique are very important for dependable embedded systems, making technologies such as drones and other autonomous systems with sophisticated embedded controllers and systems relatively common-place.
The aim of this book is to present the theoretical and practical aspects of embedded robust control design and implementation with the aid of MATLAB® and SIMULINK®. It covers methods suitable for practical implementations, combining knowledge from control system design and computer engineering to describe the entire design cycle. Three extended case studies are developed in depth: embedded control of a tank physical model; robust control of a miniature helicopter; and robust control of two-wheeled robots.
These are taken from the area of motion control but the book may be also used by designers in other areas. Some knowledge of Linear Control Theory is assumed and knowledge of C programming is desirable but to make the book accessible to engineers new to the field and to students, the authors avoid complicated mathematical proofs and overwhelming computer architecture technical details. All programs used in the examples and case studies are freely downloadable to help with the assimilation of the book contents.
This book presents developments in analysis and design techniques for control systems. Included are exciting results for feedback systems using complex variable methods, the important concept of robustness in controller design and the increasingly important topic of decentralized control for large scale systems. These and many other contributions illustrate the great activity and rapid progress which has taken place in the subject over the past few years. Only by bringing these contributions together under one cover can the practising engineer in industry and indeed the engineer in university or polytechnic keep fully informed on the 'state of the art' on a number of different fronts. Application of the theoretical developments and practical aspects of the subject are not forgotten; analysis and design of a nuclear boiler and some direct digital control system design procedures are but two topics discussed in the present book. Several of the chapters are followed by problems on the subject matter and worked solutions to most of these problems are given at the end of the book. This aspect will find favour with many readers since such contributions are often a great help in the understanding of the subject matter.
One of the main fields of study in the control of dynamical systems has been the effective control of time-varying systems with uncertain parameters and external disturbances. In contrast to stochastic adaptive controllers with identification algorithms, the deterministic control of uncertain time-varying systems has a fixed nonlinear feedback controller, which operates effectively over a specified magnitude range of a class of system variations. If the variations satisfy certain matching conditions, complete insensitivity to system uncertainties can be achieved. The two main approaches are Variables Structure and Lyapunov control. The contents of this book reflect the research output of many authors. The chapters include material of an introductory nature as well as some of the latest research results. Attention has also been focussed upon some of the main areas of application, which include electric motor drives, robotics and flight control systems. The book should prove useful to control designers, theoreticians and graduate students.
Glocal control, a term coined by Professor Shinji Hara at The University of Tokyo, represents a new framework for studying behaviour of complex dynamical systems from a feedback control perspective. A large number of dynamical components can be interconnected and interact with each other to form an integrated system with certain functionalities. Such complex systems are found in nature and have been created by man, including gene regulatory networks, neuronal circuits for memory, decision making, and motor control, bird flocking, global climate dynamics, central processing units for computers, electrical power grids, the World Wide Web, and financial markets. A common feature of these systems is that a global property or function emerges as a result of local, distributed, dynamical interactions of components. The objective of 'glocal' (global + local) control is to understand the mechanisms underlying this feature, analyze existing complex systems, and to design and create innovative systems with new functionalities. This book is dedicated to Professor Shinji Hara on the occasion of his 60th birthday, collecting the latest results by leading experts in control theories to lay a solid foundation towards the establishment of glocal control theory in the coming decades.
As control systems become more complex and are expected to perform tasks in unknown and extreme environments, they may be subject to various types of faults in their sensors, actuators or other components. It is crucial to be able to diagnose the occurrence of faults and to repair them in order to maintain, guarantee, and improve the overall safety, reliability, and performance of the systems. This book addresses the design challenges of developing and implementing novel integrated fault diagnosis and control technologies for complex linear systems.
Integrated Fault Diagnosis and Control Design of Linear Complex Systems considers linear time-invariant (LTI) systems under both time- and event-triggered frameworks. The book initially develops novel methodologies for the problem of integrated fault diagnosis and control of LTI systems to address current design challenges. The results obtained are then extended to a number of complex linear systems, specifically to Markovian jump systems as well as to cooperative multi-agent systems.
This book gives an exposition of recently developed approximate dynamic programming (ADP) techniques for decision and control in human engineered systems. ADP is a reinforcement machine learning technique that is motivated by learning mechanisms in biological and animal systems. It is connected from a theoretical point of view with both adaptive control and optimal control methods. The book shows how ADP can be used to design a family of adaptive optimal control algorithms that converge in real-time to optimal control solutions by measuring data along the system trajectories. Generally, in the current literature adaptive controllers and optimal controllers are two distinct methods for the design of automatic control systems. Traditional adaptive controllers learn online in real time how to control systems, but do not yield optimal performance. On the other hand, traditional optimal controllers must be designed offline using full knowledge of the systems dynamics. It is also shown how to use ADP methods to solve multi-player differential games online. Differential games have been shown to be important in H-infinity robust control for disturbance rejection, and in coordinating activities among multiple agents in networked teams. The focus of this book is on continuous-time systems, whose dynamical models can be derived directly from physical principles based on Hamiltonian or Lagrangian dynamics.
Prediction and Regulation by Linear Least-Square Methods was first published in 1963. This revised second edition was issued in 1983. Minnesota Archive Editions uses digital technology to make long-unavailable books once again accessible, and are published unaltered from the original University of Minnesota Press editions.During the past two decades, statistical theories of prediction and control have assumed an increasing importance in all fields of scientific research. To understand a phenomenon is to be able to predict it and to influence it in predictable ways. First published in 1963 and long out of print, Prediction and Regulation by Linear Least-Square Methods offers important tools for constructing models of dynamic phenomena. This elegantly written book has been a basic reference for researchers in many applied sciences who seek practical information about the representation and manipulation of stationary stochastic processes. Peter Whittle’s text has a devoted group of readers and users, especially among economists. This edition contains the unchanged text of the original and adds new works by the author and a foreword by economist Thomas J. Sargent.
Many realistic engineering systems are large in dimension and stiff for computation. Their analysis and control require extensive numerical algorithms. The methodology of singular perturbations and time scales (SPTS), crowned with the remedial features of order reduction and stiffness relief is a powerful technique to achieve computational simplicity.
This book presents the twin topics of singular perturbation methods and time scale analysis to problems in systems and control. The heart of the book is the singularly perturbed optimal control systems, which are notorious for demanding excessive computational costs.
The book addresses both continuous control systems (described by differential equations) and discrete control systems (characterised by difference equations). Another feature is the extensive bibliography, which will hopefully be of great help for future study and research. Also of particular interest is the categorisation of an impressive record of applications of the methodology of SPTS in a wide spectrum of fields, such as circuits and networks, fluid mechanics and flight mechanics, biology and ecology, and robotics.
This book is aimed at graduate students, applied mathematicians, scientists and engineers working in universities and industry.