A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover applications for the identification of linear and non-linear systems, the design of generalized predictive controllers (GPCs), and the control of multivariable systems.
A presentation of techniques in advanced process modelling, identification, prediction, and parameter estimation for the implementation and analysis of industrial systems. The authors cover applications for the identification of linear and non-linear systems, the design of generalized predictive controllers (GPCs), and the control of multivariable
Process Identification and PID Control enables students and researchers to understand the basic concepts of feedback control, process identification, autotuning as well as design and implement feedback controllers, especially, PID controllers. The first The first two parts introduce the basics of process control and dynamics, analysis tools (Bode plot, Nyquist plot) to characterize the dynamics of the process, PID controllers and tuning, advanced control strategies which have been widely used in industry. Also, simple simulation techniques required for practical controller designs and research on process identification and autotuning are also included. Part 3 provides useful process identification methods in real industry. It includes several important identification algorithms to obtain frequency models or continuous-time/discrete-time transfer function models from the measured process input and output data sets. Part 4 introduces various relay feedback methods to activate the process effectively for process identification and controller autotuning. Combines the basics with recent research, helping novice to understand advanced topics Brings several industrially important topics together: Dynamics Process identification Controller tuning methods Written by a team of recognized experts in the area Includes all source codes and real-time simulated processes for self-practice Contains problems at the end of every chapter PowerPoint files with lecture notes available for instructor use
Industrial Process Identification and Control Design is devoted to advanced identification and control methods for the operation of continuous-time processes both with and without time delay, in industrial and chemical engineering practice. The simple and practical step- or relay-feedback test is employed when applying the proposed identification techniques, which are classified in terms of common industrial process type: open-loop stable; integrating; and unstable, respectively. Correspondingly, control system design and tuning models that follow are presented for single-input-single-output processes. Furthermore, new two-degree-of-freedom control strategies and cascade control system design methods are explored with reference to independently-improving, set-point tracking and load disturbance rejection. Decoupling, multi-loop, and decentralized control techniques for the operation of multiple-input-multiple-output processes are also detailed. Perfect tracking of a desire output trajectory is realized using iterative learning control in uncertain industrial batch processes. All the proposed methods are presented in an easy-to-follow style, illustrated by examples and practical applications. This book will be valuable for researchers in system identification and control theory, and will also be of interest to graduate control students from process, chemical, and electrical engineering backgrounds and to practising control engineers in the process industry.
This book reviews the theoretical fundamentals of grey-box identification and puts the spotlight on MoCaVa, a MATLAB-compatible software tool, for facilitating the procedure of effective grey-box identification. It demonstrates the application of MoCaVa using two case studies drawn from the paper and steel industries. In addition, the book answers common questions which will help in building accurate models for systems with unknown inputs.
This compact and original reference and textbook presents the most important classical and modern essentials of control engineering in a single volume. It constitutes a harmonic mixture of control theory and applications, which makes the book especially useful for students, practicing engineers and researchers interested in modeling and control of processes. Well written and easily understandable, it includes a range of methods for the analysis and design of control systems.
System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text. Following an introduction on system theory, particularly in relation to model representation and model properties, the book contains four parts covering: • data-based identification – non-parametric methods for use when prior system knowledge is very limited; • time-invariant identification for systems with constant parameters; • time-varying systems identification, primarily with recursive estimation techniques; and • model validation methods. A fifth part, composed of appendices, covers the various aspects of the underlying mathematics needed to begin using the text. The book uses essentially semi-physical or gray-box modeling methods although data-based, transfer-function system descriptions are also introduced. The approach is problem-based rather than rigorously mathematical. The use of finite input–output data is demonstrated for frequency- and time-domain identification in static, dynamic, linear, nonlinear, time-invariant and time-varying systems. Simple examples are used to show readers how to perform and emulate the identification steps involved in various control design methods with more complex illustrations derived from real physical, chemical and biological applications being used to demonstrate the practical applicability of the methods described. End-of-chapter exercises (for which a downloadable instructors’ Solutions Manual is available from fill in URL here) will both help students to assimilate what they have learned and make the book suitable for self-tuition by practitioners looking to brush up on modern techniques. Graduate and final-year undergraduate students will find this text to be a practical and realistic course in system identification that can be used for assessing the processes of a variety of engineering disciplines. System Identification will help academic instructors teaching control-related to give their students a good understanding of identification methods that can be used in the real world without the encumbrance of undue mathematical detail.
This book covers recent results in the analysis, identification and control of systems described by Volterra models. Topics covered include: qualitative behavior of finite Volterra models compared and contrasted with other nonlinear model classes, structural restrictions and extensions to Volterra model class, least squares and stochastic identification approaches, model inversion issues, and direct synthesis and model predictive control design, guidelines for practical applications. Examples are drawn from Chemical, Biological and Electrical Engineering. The book is suitable as a text for a graduate control course, or as a reference for both research and practice.
Modern industrial processes and systems require adaptable advanced control protocols able to deal with circumstances demanding "judgement” rather than simple "yes/no”, "on/off” responses: circumstances where a linguistic description is often more relevant than a cut-and-dried numerical one. The ability of fuzzy systems to handle numeric and linguistic information within a single framework renders them efficacious for this purpose. Fuzzy Logic, Identification and Predictive Control first shows you how to construct static and dynamic fuzzy models using the numerical data from a variety of real industrial systems and simulations. The second part exploits such models to design control systems employing techniques like data mining. This monograph presents a combination of fuzzy control theory and industrial serviceability that will make a telling contribution to your research whether in the academic or industrial sphere and also serves as a fine roundup of the fuzzy control area for the graduate student.
Advanced Analytic Control Techniques for Thermal Systems with Heat Exchangers presents the latest research on sophisticated analytic and control techniques specific for Heat Exchangers (HXs) and heat Exchanger Networks (HXNs), such as Stability Analysis, Efficiency of HXs, Fouling Effect, Delay Phenomenon, Robust Control, Algebraic Control, Geometric Control, Optimal Control, Fuzzy Control and Artificial Intelligence techniques. Editor Libor Pekar and his team of global expert contributors combine their knowledge and experience of investigated and applied systems and processes in this thorough review of the most advanced networks, analyzing their dynamics, efficiency, transient features, physical properties, performance, feasibility, flexibility and controllability. The structural and dynamic analyses and control approaches of HXNs, as well as energy efficient manipulation techniques are discussed, in addition to the design of the control systems through the full life cycle. This equips the reader with an understanding of the relevant theory in a variety of settings and scenarios and the confidence to apply that knowledge to solve problems in an academic or professional setting.Graduate students and early-mid career professionals require a robust understanding of how to suitably design thermal systems with HXs and HXNs to achieve required performance levels, which this book offers in one consolidated reference. All examples and solved problems included have been tried and tested, and these combined with the research driven theory provides professionals, researchers and students with the most recent techniques to maximize the energy efficiency and sustainability of existing and new thermal power systems. Analyses several advanced techniques, the theoretical background of these techniques and includes models, examples and results throughout Focusses on advanced analytic and control techniques which have been investigated or applied to thermal systems with HXs and HXNs Includes practical applications and advanced ideas from leading experts in the field, as well as case studies and tested problems and solutions
