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Understanding Process Dynamics and Control (Cambridge Series in Chemical Engineering)
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About Understanding Process Dynamics And Control
Product Description Presenting a fresh look at process control, this new text demonstrates state-space approach shown in parallel with the traditional approach to explain the strategies used in industry today. Modern time-domain and traditional transform-domain methods are integrated throughout and explain the advantages and limitations of each approach; the fundamental theoretical concepts and methods of process control are applied to practical problems. To ensure understanding of the mathematical calculations involved, MATLAB® is included for numeric calculations and MAPLE for symbolic calculations, with the math behind every method carefully explained so that students develop a clear understanding of how and why the software tools work. Written for a one-semester course with optional advanced-level material, features include solved examples, cases that include a number of chemical reactor examples, chapter summaries, key terms, and concepts, as well as over 240 end-of-chapter problems, focused computational exercises and solutions for instructors. Review ‘Provides a fresh perspective through the integrated coverage of modern state-space and traditional transfer function approaches. The mathematical derivations are detailed and accessible, aiding clear understanding of the basic as well as the more advanced topics.’ Prodromos Daoutidis, University of Minnesota ‘Breaking new ground in the crowded field of process control textbooks, this book provides the foundation for teaching a modern undergraduate process control course in the twenty-first century. It is exceptionally well written and organized, and includes numerous examples, making it a must-have for all process control researchers, students and engineers.’ Panagiotis D. Christofides, University of California, Los Angeles Book Description A fresh look to process control. State-space and traditional approaches presented in parallel with relevant computer software. About the Author Costas Kravaris is Professor of Chemical Engineering at Texas A&M University, USA. He has over 35 years of in teaching experience in process dynamics and control classes at both undergraduate and graduate level. He is an active researcher is nonlinear control, nonlinear state estimation and nonlinear model reduction, with applications to chemical processes. Ioannis K. Kookos is Professor of Process Systems Engineering, in the Department Chemical Engineering at the University of Patras, Greece. He received his BSc in Chemical Engineering from the National Technical University of Athens, Greece and his MSc (1994) and PhD (2001) in Process Systems Engineering from Imperial College, London (Centre for PSE). He then worked as a lecturer at the University of Manchester, Department of Chemical Engineering.
