Process Dynamics and ControlThe new 4th edition of Seborg’s Process Dynamics and Control provides full topical coverage for process control courses in the chemical engineering curriculum, emphasizing how process control and its related fields of process modeling and optimization are essential to the development of high-value products. A principal objective of this new edition is to describe modern techniques for control processes, with an emphasis on complex systems necessary to the development, design, and operation of modern processing plants. Control process instructors can cover the basic material while also having the flexibility to include advanced topics. |
Contents
Part Two Dynamic Behavior of Processes | 38 |
Part Three Feedback and Feedforward Control | 123 |
Part Four Advanced Process Control | 279 |
Part Five Applications to Biological Systems | 435 |
Digital Process Control Systems Hardware and Software | 464 |
Review of Thermodynamic Concepts for Conservation Equations | 478 |
Control Simulation Software | 480 |
Instrumentation Symbols | 487 |
Process Control Modules | 489 |
Review of Basic Concepts From Probability and Statistics | 491 |
Index | 495 |
EULA | 503 |
Other editions - View all
Process Dynamics and Control Dale E. Seborg,Thomas F. Edgar,Duncan A. Mellichamp,Francis J. Doyle, III Limited preview - 2016 |
Process Dynamics and Control Dale E. Seborg,Duncan A. Mellichamp,Thomas F. Edgar,Francis J. Doyle, III Limited preview - 2010 |
Common terms and phrases
alarm analysis batch batch process block diagram Bode plot calculated Chapter characteristic equation chemical closed-loop response closed-loop system closed-loop transfer function composition consider constant constraints control chart control loop control strategy control system control valve controlled variable controller output controller settings delay denote derived distillation column disturbance variable dynamic model equation example feed feedback control feedforward control Figure filter first-order flow rate heat inlet input integral Laplace transform linear liquid level manipulated variable MATLAB measured method Model Predictive Control nonlinear nonlinear regression operating optimization output variables parameters PID controller pressure process control process model process variables proportional controller reactor result second-order Section sensor set point set-point changes shown in Fig signal simulation Simulink SOLUTION specified stability steady-state gain step change step response stirred-tank stream tank temperature tion transfer function model transmitter tuning unit step zero