Identification of industrial process dynamics
Author | : |
Publisher | : |
Total Pages | : 14 |
Release | : 1974 |
Genre | : |
ISBN | : |
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Author | : |
Publisher | : |
Total Pages | : 14 |
Release | : 1974 |
Genre | : |
ISBN | : |
Author | : Ivar Gustavsson |
Publisher | : |
Total Pages | : 14 |
Release | : 1974 |
Genre | : |
ISBN | : |
Author | : Tao Liu |
Publisher | : Springer Science & Business Media |
Total Pages | : 487 |
Release | : 2011-11-16 |
Genre | : Technology & Engineering |
ISBN | : 0857299778 |
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.
Author | : Dale E. Seborg |
Publisher | : John Wiley & Sons |
Total Pages | : 512 |
Release | : 2016-09-13 |
Genre | : Technology & Engineering |
ISBN | : 1119285917 |
The new 4th edition of Seborg’s Process Dynamics Control provides full topical coverage for process control courses in the chemical engineering curriculum, emphasizing how process control and its related fields of process modeling and optimization are essential to the development of high-value products. A principal objective of this new edition is to describe modern techniques for control processes, with an emphasis on complex systems necessary to the development, design, and operation of modern processing plants. Control process instructors can cover the basic material while also having the flexibility to include advanced topics.
Author | : Dale E. Seborg |
Publisher | : John Wiley & Sons |
Total Pages | : 356 |
Release | : 2010-04-12 |
Genre | : Technology & Engineering |
ISBN | : 0470128674 |
This third edition provides chemical engineers with process control techniques that are used in practice while offering detailed mathematical analysis. Numerous examples and simulations are used to illustrate key theoretical concepts. New exercises are integrated throughout several chapters to reinforce concepts. Up-to-date information is also included on real-time optimization and model predictive control to highlight the significant impact these techniques have on industrial practice. And chemical engineers will find two new chapters on biosystems control to gain the latest perspective in the field.
Author | : Babatunde Ayodeji Ogunnaike |
Publisher | : Topics in Chemical Engineering |
Total Pages | : 1260 |
Release | : 1994 |
Genre | : Technology & Engineering |
ISBN | : 9780195091199 |
This text offers a modern view of process control in the context of today's technology. It provides the standard material in a coherent presentation and uses a notation that is more consistent with the research literature in process control. Topics that are unique include a unified approach to model representations, process model formation and process identification, multivariable control, statistical quality control, and model-based control. This book is designed to be used as an introductory text for undergraduate courses in process dynamics and control. In addition to chemical engineering courses, the text would also be suitable for such courses taught in mechanical, nuclear, industrial, and metallurgical engineering departments. The material is organized so that modern concepts are presented to the student but details of the most advanced material are left to later chapters. The text material has been developed, refined, and classroom tested over the last 10-15 years at the University of Wisconsin and more recently at the University of Delaware. As part of the course at Wisconsin, a laboratory has been developed to allow the students hands-on experience with measurement instruments, real time computers, and experimental process dynamics and control problems.
Author | : Chao Shang |
Publisher | : Springer |
Total Pages | : 154 |
Release | : 2018-02-22 |
Genre | : Technology & Engineering |
ISBN | : 9811066779 |
This thesis develops a systematic, data-based dynamic modeling framework for industrial processes in keeping with the slowness principle. Using said framework as a point of departure, it then proposes novel strategies for dealing with control monitoring and quality prediction problems in industrial production contexts. The thesis reveals the slowly varying nature of industrial production processes under feedback control, and integrates it with process data analytics to offer powerful prior knowledge that gives rise to statistical methods tailored to industrial data. It addresses several issues of immediate interest in industrial practice, including process monitoring, control performance assessment and diagnosis, monitoring system design, and product quality prediction. In particular, it proposes a holistic and pragmatic design framework for industrial monitoring systems, which delivers effective elimination of false alarms, as well as intelligent self-running by fully utilizing the information underlying the data. One of the strengths of this thesis is its integration of insights from statistics, machine learning, control theory and engineering to provide a new scheme for industrial process modeling in the era of big data.
Author | : Govind Das Nageshwar |
Publisher | : PHI Learning Pvt. Ltd. |
Total Pages | : 344 |
Release | : 2011 |
Genre | : Chemical process control |
ISBN | : 9788120344051 |
Author | : M A. Choudhury |
Publisher | : |
Total Pages | : 229 |
Release | : 1978 |
Genre | : |
ISBN | : |
The analysis of a chemical plant under computer control is performed. A twin computer system carries out direct digital control of the flow of the reactants to the plant and maintains a certain temperature profile which is necessary to produce a good quality chemical product. Data is logged by the computer system giving valuable information which could be used to improve the control scheme. A suite of programs, named CAROL, was developed and stored on the School of Control Engineering's HP2100A computer. This package enables to decode the normal operating records obtained from the DDC (direct digital control) computer records and display the data in time series form. After choosing the suitable time series of the process variables by CAROL package, CORMAT, an identification package written at Bradford University, is used for identification and modelling of the process dynamics. Computer control analysis and design of important process loops is performed by CAIAD, computer aided design package written at Bradford University.
Author | : Rolf Isermann |
Publisher | : Springer Science & Business Media |
Total Pages | : 705 |
Release | : 2010-11-22 |
Genre | : Technology & Engineering |
ISBN | : 3540788794 |
Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.