The purpose of this book is to convey to undergraduate students an understanding of those areas of process control that all chemical engineers need to know. The presentation is concise, readable and restricted to only essential elements. The methods presented have been successfully applied in industry to solve real problems. Analysis of closedloop dynamics in the time, Laplace, frequency and sample-data domains are covered. Designing simple regulatory control systems for multivariable processes is discussed. The practical aspects of process control are presented sizing control valves, tuning controllers, developing control structures and considering interaction between plant design and control. Practical simple identification methods are covered.

The purpose of this book is to convey to undergraduate students an understanding of those areas of process control that all chemical engineers need to know. The presentation is concise, readable and restricted to only essential elements. The methods presented have been successfully applied in industry to solve real problems. Analysis of closedloop dynamics in the time, Laplace, frequency and sample-data domains are covered. Designing simple regulatory control systems for multivariable processes is discussed. The practical aspects of process control are presented sizing control valves, tuning controllers, developing control structures and considering interaction between plant design and control. Practical simple identification methods are covered.

Chemical Engineering Process Simulation, Second Edition guides users through chemical processes and unit operations using the main simulation software used in the industrial sector. The book helps predict the characteristics of a process using mathematical models and computer-aided process simulation tools, as well as how to model and simulate process performance before detailed process design takes place. Content coverage includes steady-state and dynamic simulation, process design, control and optimization. In addition, readers will learn about the simulation of natural gas, biochemical, wastewater treatment and batch processes. - Provides an updated and expanded new edition that contains 60-70% new content - Guides readers through chemical processes and unit operations using the primary simulation software used in the industrial sector - Covers the fundamentals of process simulation, theory and advanced applications - Includes case studies of various difficulty levels for practice and for applying developed skills - Features step-by-step guides to using UniSim Design, SuperPro Designer, Symmetry, Aspen HYSYS and Aspen Plus for process simulation novices

This book offers a comprehensive coverage of process simulation and flowsheeting, useful for undergraduate students of Chemical Engineering and Process Engineering as theoretical and practical support in Process Design, Process Simulation, Process Engineering, Plant Design, and Process Control courses. The main concepts related to process simulation and application tools are presented and discussed in the framework of typical problems found in engineering design. The topics presented in the chapters are organized in an inductive way, starting from the more simplistic simulations up to some complex problems.

In this textbook, the author teaches readers how to model and simulate a unit process operation through developing mathematical model equations, solving model equations manually, and comparing results with those simulated through software. It covers both lumped parameter systems and distributed parameter systems, as well as using MATLAB and Simulink to solve the system model equations for both. Simplified partial differential equations are solved using COMSOL, an effective tool to solve PDE, using the fine element method. This book includes end of chapter problems and worked examples, and summarizes reader goals at the beginning of each chapter.

Master process control hands on, through practical examples and MATLAB(R) simulations This is the first complete introduction to process control that fully integrates software tools--enabling professionals and students to master critical techniques hands on, through computer simulations based on the popular MATLAB environment. Process Control: Modeling, Design, and Simulation teaches the field's most important techniques, behaviors, and control problems through practical examples, supplemented by extensive exercises--with detailed derivations, relevant software files, and additional techniques available on a companion Web site. Coverage includes: Fundamentals of process control and instrumentation, including objectives, variables, and block diagrams Methodologies for developing dynamic models of chemical processes Dynamic behavior of linear systems: state space models, transfer function-based models, and more Feedback control; proportional, integral, and derivative (PID) controllers; and closed-loop stability analysis Frequency response analysis techniques for evaluating the robustness of control systems Improving control loop performance: internal model control (IMC), automatic tuning, gain scheduling, and enhancements to improve disturbance rejection Split-range, selective, and override strategies for switching among inputs or outputs Control loop interactions and multivariable controllers An introduction to model predictive control (MPC) Bequette walks step by step through the development of control instrumentation diagrams for an entire chemical process, reviewing common control strategies for individual unit operations, then discussing strategies for integrated systems. The book also includes 16 learning modules demonstrating how to use MATLAB and SIMULINK to solve several key control problems, ranging from robustness analyses to biochemical reactors, biomedical problems to multivariable control.

This book offers a modern view of process control in the context of today's technology. It provides innovative chapters on the growth of educational, scientific, and industrial research among chemical engineers. It presents experimental data on thermodynamics and provides a broad understanding of the main computational techniques used for chemical

Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.