Advanced Control of Chemical Processes 1994

Advanced Control of Chemical Processes 1994
Author: D. Bonvin
Publisher: Elsevier
Total Pages: 561
Release: 2014-05-23
Genre: Technology & Engineering
ISBN: 1483297594

This publication brings together the latest research findings in the key area of chemical process control; including dynamic modelling and simulation - modelling and model validation for application in linear and nonlinear model-based control: nonlinear model-based predictive control and optimization - to facilitate constrained real-time optimization of chemical processes; statistical control techniques - major developments in the statistical interpretation of measured data to guide future research; knowledge-based v model-based control - the integration of theoretical aspects of control and optimization theory with more recent developments in artificial intelligence and computer science.

Methods of Model Based Process Control

Methods of Model Based Process Control
Author: R. Berber
Publisher: Springer Science & Business Media
Total Pages: 814
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 9401101353

Model based control has emerged as an important way to improve plant efficiency in the process industries, while meeting processing and operating policy constraints. The reader of Methods of Model Based Process Control will find state of the art reports on model based control technology presented by the world's leading scientists and experts from industry. All the important issues that a model based control system has to address are covered in depth, ranging from dynamic simulation and control-relevant identification to information integration. Specific emerging topics are also covered, such as robust control and nonlinear model predictive control. In addition to critical reviews of recent advances, the reader will find new ideas, industrial applications and views of future needs and challenges. Audience: A reference for graduate-level courses and a comprehensive guide for researchers and industrial control engineers in their exploration of the latest trends in the area.

Nonlinear Model-based Process Control

Nonlinear Model-based Process Control
Author: Rashid M. Ansari
Publisher: Springer Science & Business Media
Total Pages: 248
Release: 2012-12-06
Genre: Science
ISBN: 144710739X

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The last decade has seen considerable interest in reviving the fortunes of non linear control. In contrast to the approaches of the 60S, 70S and 80S a very pragmatic agenda for non-linear control is being pursued using the model-based predictive control paradigm. This text by R. Ansari and M. Tade gives an excellent synthesis of this new direction. Two strengths emphasized by the text are: (i) four applications found in refinery processes are used to give the text a firm practical continuity; (ii) a non-linear model-based control architecture is used to give the method a coherent theoretical framework.

Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (DYCORD'95)

Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (DYCORD'95)
Author: J.B. Rawlings
Publisher: Elsevier
Total Pages: 513
Release: 2014-05-23
Genre: Technology & Engineering
ISBN: 1483296881

Three important areas of process dynamics and control: chemical reactors, distillation columns and batch processes are the main topics of discussion and evaluation at the IFAC Symposium on Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (DYCORD '95). This valuable publication was produced from the latest in the series, providing a detailed assessment of developments of key technologies within the field of process dynamics and control.

Neural Network Applications in Control

Neural Network Applications in Control
Author: George William Irwin
Publisher: IET
Total Pages: 320
Release: 1995
Genre: Computers
ISBN: 9780852968529

The aim is to present an introduction to, and an overview of, the present state of neural network research and development, with an emphasis on control systems application studies. The book is useful to a range of levels of reader. The earlier chapters introduce the more popular networks and the fundamental control principles, these are followed by a series of application studies, most of which are industrially based, and the book concludes with a consideration of some recent research.

Model-Based Predictive Control

Model-Based Predictive Control
Author: J.A. Rossiter
Publisher: CRC Press
Total Pages: 323
Release: 2017-07-12
Genre: Technology & Engineering
ISBN: 135198859X

Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive control from its base mathematical foundation, but delivers the subject matter in a readable, intuitive style. The author writes in layman's terms, avoiding jargon and using a style that relies upon personal insight into practical applications. This detailed introduction to predictive control introduces basic MPC concepts and demonstrates how they are applied in the design and control of systems, experiments, and industrial processes. The text outlines how to model, provide robustness, handle constraints, ensure feasibility, and guarantee stability. It also details options in regard to algorithms, models, and complexity vs. performance issues.

Non-linear Predictive Control

Non-linear Predictive Control
Author: Basil Kouvaritakis
Publisher: IET
Total Pages: 277
Release: 2001-10-26
Genre: Mathematics
ISBN: 0852969848

The advantage of model predictive control is that it can take systematic account of constraints, thereby allowing processes to operate at the limits of achievable performance. Engineers in academia, industry, and government from the US and Europe explain how the linear version can be adapted and applied to the nonlinear conditions that characterize the dynamics of most real manufacturing plants. They survey theoretical and practical trends, describe some specific theories and demonstrate their practical application, derive strategies that provide appropriate assurance of closed-loop stability, and discuss practical implementation. Annotation copyrighted by Book News, Inc., Portland, OR

Intelligent Hybrid Systems

Intelligent Hybrid Systems
Author: Da Ruan
Publisher: Springer Science & Business Media
Total Pages: 364
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461561914

Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms is an organized edited collection of contributed chapters covering basic principles, methodologies, and applications of fuzzy systems, neural networks and genetic algorithms. All chapters are original contributions by leading researchers written exclusively for this volume. This book reviews important concepts and models, and focuses on specific methodologies common to fuzzy systems, neural networks and evolutionary computation. The emphasis is on development of cooperative models of hybrid systems. Included are applications related to intelligent data analysis, process analysis, intelligent adaptive information systems, systems identification, nonlinear systems, power and water system design, and many others. Intelligent Hybrid Systems: Fuzzy Logic, Neural Networks, and Genetic Algorithms provides researchers and engineers with up-to-date coverage of new results, methodologies and applications for building intelligent systems capable of solving large-scale problems.

Receding Horizon Control

Receding Horizon Control
Author: Wook Hyun Kwon
Publisher: Springer Science & Business Media
Total Pages: 388
Release: 2005-10-04
Genre: Technology & Engineering
ISBN: 1846280176

Easy-to-follow learning structure makes absorption of advanced material as pain-free as possible Introduces complete theories for stability and cost monotonicity for constrained and non-linear systems as well as for linear systems In co-ordination with MATLABĀ® files available from springeronline.com, exercises and examples give the student more practice in the predictive control and filtering techniques presented

Issues of Fault Diagnosis for Dynamic Systems

Issues of Fault Diagnosis for Dynamic Systems
Author: Ron J. Patton
Publisher: Springer Science & Business Media
Total Pages: 632
Release: 2000-03-29
Genre: Computers
ISBN: 9783540199687

Since the time our first book Fault Diagnosis in Dynamic Systems: The ory and Applications was published in 1989 by Prentice Hall, there has been a surge in interest in research and applications into reliable methods for diag nosing faults in complex systems. The first book sold more than 1,200 copies and has become the main text in fault diagnosis for dynamic systems. This book will follow on this excellent record by focusing on some of the advances in this subject, by introducing new concepts in research and new application topics. The work cannot provide an exhaustive discussion of all the recent research in fault diagnosis for dynamic systems, but nevertheless serves to sample some of the major issues. It has been valuable once again to have the co-operation of experts throughout the world working in industry, gov emment establishments and academic institutions in writing the individual chapters. Sometimes dynamical systems have associated numerical models available in state space or in frequency domain format. When model infor mation is available, the quantitative model-based approach to fault diagnosis can be taken, using the mathematical model to generate analytically redun dant alternatives to the measured signals. When this approach is used, it becomes important to try to understand the limitations of the mathematical models i. e. , the extent to which model parameter variations occur and the effect of changing the systems point of operation.