Section headings and selected papers: Survey Papers. Stability criteria for chemical reactors, V. Balakotaiah & D. Kodra. Dynamics and control of distillation columns - a critical survey, S. Skogestad. Modeling and control of polymerization reactors, W. H. Ray. Modeling and control of microelectronics materials processing, T. F. Edgar et al. Chemical Reactors Modelling, Estimation, and Control. A data-based process modeling approach and its applications, S. J. Qin & T. J. McAvoy. Dynamics of a packed bed reactor with reactant recycle, H. Brabrand & S. B. Jorgensen. Adaptive linearizing control of non-isothermal reactors, D. Dochain. Reliable control of chemical processes with a supervisory knowledge-based system, M. R. Basila & A. Cinar. A comparison of strategies for the control of a polypropene reactor, B. Lie & J. G. Balchen. Distillation Columns Modelling, Estimation and Control. An analytical approach to modelling in distillation control, T. Lüder & G. Wozny. Control structures for a sidestream distillation column separating a ternary mixture, A. Koggersbol & S. B. Jorgensen. Feedforward/feedback control of a binary high purity distillation column, J. Broll & H. Gelbe. Combining adaptive and neural control for distillation control, M. Roele & K. Warwick. Batch Processes Modelling, and Control. Discrete-event controlled systems in the chemical processing industry, H. A. Preisig. The design and synthesis of batch/semicontinuous processes, In-Beum Lee et al. Dissolved oxygen control using an automatic tuning PID controller, K. O. Jones et al. Operation strategies for reverse-osmosis membrane fouling in dairy industry, A. J. B. Boxtel & Z. E. H. Otten. General Systems, Modelling, Estimation and Control. Hybrid neural network/algorithmic approaches to system identification, A. F. Konar et al. A nonlinea
In addition to the three main themes: chemical reactors, distillation columns, and batch processes this volume also addresses some of the new trends in dynamics and control methodology such as model based predictive control, new methods for identification of dynamic models, nonlinear control theory and the application of neural networks to identification and control. Provides a useful reference source of the major advances in the field.
For systems and process control engineers.
- No. of pages:
- © Pergamon 1993
- 13th April 1993
- eBook ISBN:
Department of Engineering Cybernetics, The Norwegian Institute of Technology, Trondheim, Norway
University of Wisconsin-Madison, Wisconsin, USA