Adaptive Control of Chemical Processes 1985 by International Federation of Automatic Control, Heinz

By International Federation of Automatic Control, Heinz Unbehauen

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1) Based on: - Qualitative a priori knowledge of the interactions between quantities in a certain process 27 28 G. E. Bortolotto and S. ) - Control objective 2) Decide upon: - Set of measurements and control inputs - Sampling interval - Model structure However, going from 1) to 2) is not always straightforward. In most cases, the main difficulty is how the information 1) shared between process engineers and technicians can be effectively transferred to the control engineer such that the decisions in 2) can be made.

The experimental results for increasing and decreasing dead time are shown in F i g s . 7 and 8. Fig. In F i g . 6, w e note a gradual degradation in control performance after 1 0 0 m i n u t e s . T h e P I controller in the Smith Predictor scheme w a s tuned c o n s e r v a tively, and t h e r e f o r e , m a i n t a i n s stability; h o w ever, some of the benefit of dead time compensation In F i g . 7, local stability is l o s t , and is lost. the final element activity s a t u r a t e s . N e x t , a self-tuning regulator based o n the m i n i m u m v a r i a n c e controller w i t h fixed p r e d i c t i o n step w a s tested.

Dissertation, Princeton University. Ydstie, B. , L. S. Kershenbaum, and R. W. H. Sargent (1982). Theory and Application of a Robust Self-tuning Regulator. Report of Dept. of Chem. Eng. & Chem. , Imperial College. Copyright © IFAC Adaptive Control of Chemical Processes, Frankfurt am Main, 1985 ADAPTIVE CONTROL OF A RECYCLE REACTOR G. E. Bortolotto and S. Bay j0rgensen Instituttet for Kemiteknik, Danmarks Tekniske H0jskole, 2800 Lyngby, Denmark Abstract. A MIMO self tuning controller (MIMOSC) with an explicit model structure is applied to control a fixed bed chemical reactor with recirculation of unconverted reactants.

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