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This symposium aims to explore the current state of the art in control of industrial processes in the field of extraction and processing of metals and materials. New sensor technologies, more advanced real-time models, and faster computers are enabling better control systems for these processes. Specific topics include but are not limited to: (1) novel sensors for hostile-environment materials processes, such as online inclusion detection, temperature, and velocity in molten materials, surface condition of hot moving products, etc.; (2) innovative online sampling and analysis techniques, (3) models for real-time process control and quality monitoring systems; (4) process automation, scheduling, and plant-wide logistics optimization, (5) control of composition, temperature, microstructure, and morphology in sintering, smelting, refining, solidification, reheating, deformation, and transport of ores, slags, mattes, metals, materials, and aqueous solutions; (6) prediction, monitoring, control, and optimization of process parameters in these systems; (7) control in manufacturing processes, including casting, annealing, forging, rolling, extrusion, powder metallurgy, electronic materials, welding, etc.; (8) control of impurities and environmentally undesirable components in product and waste streams.
This book is part I of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 55 papers in this volume are organized in topical sections on intelligent modeling, monitoring, and control of complex nonlinear systems; autonomy-oriented computing and intelligent agents; advanced theory and methodology in fuzzy systems and soft computing; computational intelligence in utilization of clean and renewable energy resources; intelligent modeling, control and supervision for energy saving and pollution reduction; intelligent methods in developing vehicles, engines and equipments; computational methods and intelligence in modeling genetic and biochemical networks and regulation.
A practical guide for understanding and implementing industrial control strategies. Highly practical and applied, this Third Edition of Smith and Corripio's Principles and Practice of Automatic Process Control continues to present all the necessary theory for the successful practice of automatic process control. The authors discuss both introductory and advanced control strategies, and show how to apply those strategies in industrial examples drawn from their own professional practice. Now revised, this Third Edition features: * Expanded coverage of the development of dynamic balances (Chapter 3) * A new chapter on modeling and simulation (Chapter 13) * More extensive discussion of distributive control systems * New tuning exercises (Appendix D) * Guidelines for plant-wide control and two new design case studies (Appendix B) * New operating case studies (Appendix E) * Book Website containing simulations to practice the tuning of feedback controllers, cascade controllers, and feedforward controllers, and the MATLAB(r) files for simulation examples and problem With this text, you can: * Learn the mathematical tools used in the analysis and design of process control systems. * Gain a complete understanding of the steady state behavior of processes. * Develop dynamic mathematical process models that will help you in the analysis, design, and operation of control systems. * Understand how the basic components of control systems work. * Design and tune feedback controllers. * Apply a variety of techniques that enhance feedback control, including cascade control, ratio control, override control, selective control, feedforward control, multivariable control, and loop interaction. * Master the fundamentals of dynamic simulation of process control systems using MATLAB.
Process Control System Fault Diagnosis: A Bayesian Approach Ruben T. Gonzalez, University of Alberta, Canada Fei Qi, Suncor Energy Inc., Canada Biao Huang, University of Alberta, Canada Data-driven Inferential Solutions for Control System Fault Diagnosis A typical modern process system consists of hundreds or even thousands of control loops, which are overwhelming for plant personnel to monitor. The main objectives of this book are to establish a new framework for control system fault diagnosis, to synthesize observations of different monitors with a prior knowledge, and to pinpoint possible abnormal sources on the basis of Bayesian theory. Process Control System Fault Diagnosis: A Bayesian Approach consolidates results developed by the authors, along with the fundamentals, and presents them in a systematic way. The book provides a comprehensive coverage of various Bayesian methods for control system fault diagnosis, along with a detailed tutorial. The book is useful for graduate students and researchers as a monograph and as a reference for state-of-the-art techniques in control system performance monitoring and fault diagnosis. Since several self-contained practical examples are included in the book, it also provides a place for practicing engineers to look for solutions to their daily monitoring and diagnosis problems. Key features: • A comprehensive coverage of Bayesian Inference for control system fault diagnosis. • Theory and applications are self-contained. • Provides detailed algorithms and sample Matlab codes. • Theory is illustrated through benchmark simulation examples, pilot-scale experiments and industrial application. Process Control System Fault Diagnosis: A Bayesian Approach is a comprehensive guide for graduate students, practicing engineers, and researchers who are interests in applying theory to practice.
Stringent legislation is forcing manufacturing industry to be aware of the impact its operations have on the environment, in order to control and reduce the affect of those operations. Increasingly sophisticated equipment is required for this monitoring, and development of that equipment and strategies for its use is a multi-disciplinary field involving chemists, analytical scientists and engineers. This volume is divided into two parts, the first introducing the reader to the various sensor systems and illustrating the advantages and disadvantages those systems have for monitoring programmes, and the second introducing the problems associated with environmental monitoring, and showing how the sensors discussed in the first section can be applied to produce a thorough monitoring programme.
This collection features papers presented at the 148th Annual Meeting & Exhibition of The Minerals, Metals & Materials Society.
This book is focused on the development of rigorous, yet practical, methods for the design of advanced process control systems to improve process operational safety and cybersecurity for a wide range of nonlinear process systems. Process Operational Safety and Cybersecurity develops designs for novel model predictive control systems accounting for operational safety considerations, presents theoretical analysis on recursive feasibility and simultaneous closed-loop stability and safety, and discusses practical considerations including data-driven modeling of nonlinear processes, characterization of closed-loop stability regions and computational efficiency. The text then shifts focus to the design of integrated detection and model predictive control systems which improve process cybersecurity by efficiently detecting and mitigating the impact of intelligent cyber-attacks. The book explores several key areas relating to operational safety and cybersecurity including: machine-learning-based modeling of nonlinear dynamical systems for model predictive control; a framework for detection and resilient control of sensor cyber-attacks for nonlinear systems; insight into theoretical and practical issues associated with the design of control systems for process operational safety and cybersecurity; and a number of numerical simulations of chemical process examples and Aspen simulations of large-scale chemical process networks of industrial relevance. A basic knowledge of nonlinear system analysis, Lyapunov stability techniques, dynamic optimization, and machine-learning techniques will help readers to understand the methodologies proposed. The book is a valuable resource for academic researchers and graduate students pursuing research in this area as well as for process control engineers. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
From fundamentals to plant operations, Albright's Chemical Engineering Handbook offers a thorough, yet succinct guide to day-to-day methods and calculations used in chemical engineering applications. Leaders from an exceptional diversity of specialties provide a clear review of basic information, case examples, and references to additional information. They discuss essential principles, calculations, and key issues such as reaction engineering, process control and design, waste disposal, and electrochemical and biochemical engineering. The final chapters cover aspects of patents, intellectual property, communications, and ethics that are most relevant to engineers.
Designed for graduate and upper-level undergraduate engineering students, this is an introduction to control systems, their functions, and their current role in engineering design. Organized from a design rather than an analysis viewpoint, it shows students how to carry out practical engineering design on all types of control systems. Covers basic analysis, operating and design techniques as well as hardware/software implementation. Includes case studies.