William L. Luyben

Practical distillation control

Techniques and methods Methods: Rigorous modelling and conventional simulation Approximate and simplified models Plant-wide process control simulation Selection of controller structure Control structures, consistency and transformations Diagonal controller tuning Dynamic matrix control multivariable controllers Distillation expert systems Robust control case studies Experimental comparison of control structures Industrial experience with double quality control Control of distillation columns via distributed control systems Process design and control of extractive distillation Control by tray temperature of extractive distillation Distillation control in plant-wide control environment Model-based control Superfractionator control Control of vapor recompression distillation columns Heat-integrated columns Batch distillation.

Expert multivariable control

Abstract Multivariable control techniques have not been as widely adopted in process plants as their developers had hoped and expected. This can be attributed to their dependency on an accurate process model and their inability to effectively handle abnormal conditions. To safeguard against such shortcomings, an expert multivariable controller (EMC) is designed to make the control of multivariable processes more effective and fail-safe. It diagnoses process malfunctions and makes appropriate changes to the controller structure, control algorithms and control parameters. The controller uses plant-independent control systems knowledge as well as process specific knowledge. Its design is facilitated by using artificial intelligence (AI) techniques. The application of this controller to a distillation process is demonstrated.