The Canadian Systems & Control community is at the forefront of chemical engineering education. We recommend the following textbooks and educational materials which have been developed by our members.
Prof. Thomas A. Adams II, McMaster University
Discover how to solve challenging chemical engineering problems with Aspen Plus – in just 24 hours, and with no prior experience. Developed at McMaster University over a sevenyear period, the book features visual guides to using detailed mathematical models for a wide range of chemical process equipment, including heat exchangers, pumps, compressors, turbines, distillation columns, absorbers, strippers, and chemical reactors. Learn Aspen Plus in 24 Hours shows, step-by-step, how to configure and use Aspen Plus v9.0 and apply its powerful features to the design, operation, and optimization of safe, profitable manufacturing facilities. You will learn how to build process models and accurately simulate those models without performing tedious calculations. Divided into 12 two-hour lessons, the guide offers downloadable Aspen Plus simulations, and solutions to in-text problems.
- Contains a valuable index that lists software icons and commands used in the book
- Features helpful and time-saving links to instructional videos and technical content
- Instructs how to integrate your simulation with other supporting software such as Aspen Capital Cost Estimator, Aspen Energy Analyzer, and Microsoft Excel.
- Written by an Aspen Plus power-user and leading researcher in chemical process simulations
Prof. Yuri A. W. Shardt, the Technical University of Ilmenau
- Covers all concepts required by the American Fundamentals of Engineering Examination
- Helps the reader perform correct data analysis by providing detailed guidance frameworks in addition to the conceptual presentation
- Emphasizes examples relevant to chemical and process engineers especially those new to statistical analysis
- Microsoft Excel Templates facilitate the use of the methods presented without requiring the practitioner to have access to specialized software
- Generalized exposition of results means they can be put to use in the widest range of applications possible
- Integrative approach to system identification, linear regression and statistical theory helps the reader to understand the similarities and differences in the methods used
Prof. Prashant Mhaskar, McMaster University
Prof. Jinfeng Liu, University of Alberta
Prof. Panagiotis Christofides, University of California, Los Angeles
This book presents rigorous, yet practical, methods for the design and applications of fault-tolerant control methods. Beginning with a review of recent results and control related concepts, the book presents integrated fault-detection and isolation and safe-parking methods to handle actuator faults while accounting for process nonlinearity. Then, the book illustrates the use of these concepts in controller design and classical control monitoring. Subsequently, the book focuses on sensor related issues, resulting both from sensor failures and asynchronous measurements. The fault-tolerant control methods are applied to nonlinear chemical processes systems and their effectiveness and performance are evaluated through detailed simulations. Key features include:
- Includes new techniques for fault-detection and isolation and fault tolerant control designs that are not included in other books.
- Provides insight and fundamental understanding into fault-detection and isolation and fault-tolerant control
- Illustrates the application of the control system designs to chemical process examples of industrial interest.
- Contains a rich collection of new research topics and references to significant recent work.
The book requires basic knowledge of differential equations, linear and nonlinear control theory, and optimization methods and is intended for researchers, graduate students, and process control engineers. Throughout the book, practical implementation issues are discussed to help engineers and researchers understand the application of the methods in greater depth.
Prof. Thomas E. Marlin, McMaster University
Dr. Marlin’s learning materials on Process Control at the undergraduate level is now available for free, including all workshop materials and a digital copy of the textbook. The extensive course website includes everything you need to teach, or take, the course! This is a great resource for flipping the classroom. Features include:
- Updated and enhanced content (2016)
- Free textbook
- Course outline, including suggested schedule
- Lecture slides – including audio recorded by Prof. Marlin
- Workshops guides and slides for instructors
- Supplementary material on instrumentation for process control
Kevin Dunn, TU Delft
Kevin Dunn’s critically acclaimed (and free!) Massive Open Online Course (MOOC) on Experimentation for Improvement earned him the President’s Award for Teaching Excellence at McMaster University. The MOOC uses his free textbook, Process Improvement Using Data. The textbook has been used at a number of universities for basic and advanced Engineering Statistics courses, and all course materials, lectures notes, assignments and exams, with full solutions are available. The book includes topics such as:
- Visualizing process data
- University data analysis
- Process monitoring
- Least squares modelling
- Design and analysis of experiments
- Latent variable modelling
Prof. Simant Upreti, Ryerson University
- Presents the necessary mathematical background using numerous examples
- Includes key mathematical results along with their derivations
- Focuses on problem formulation and solving
- Incorporates detailed computational algorithms and solutions of several example problems
- Devotes a whole chapter to optimal periodic control
- Contains end-of-chapter bibliographies and exercises
Prof. Simant Upreti, Ryerson University
- Get a solid grasp of “under-the-hood” mathematical results
- Develop models of sophisticated processes
- Transform models to different geometries and domains as appropriate
- Utilize various model simplification techniques
- Learn simple and effective computational methods for model simulation
- Intensify the effectiveness of their research