Download Advanced control of chemical processes (ADCHEM '94) : IFAC by D Bonvin; International Federation of Automatic Control PDF

By D Bonvin; International Federation of Automatic Control

This e-book brings jointly the most recent learn findings within the key sector of chemical procedure regulate; together with dynamic modelling and simulation - modelling and version validation for program in linear and nonlinear model-based keep an eye on: nonlinear model-based predictive regulate and optimization - to facilitate limited real-time optimization of chemical tactics; statistical regulate techniques - significant advancements within the statistical interpretation of measured info to steer destiny study; knowledge-based v model-based control - the combination of theoretical elements of keep watch over and optimization idea with newer advancements in synthetic intelligence and desktop technological know-how.

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Additional info for Advanced control of chemical processes (ADCHEM '94) : IFAC symposium, Kyoto, Japan, 25-27 May 1994

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II _, · · x ' ' x '. ' )( '· lC ... .... 5 Response of MPC to disturbance 139 0 2 4 ... ---- - - - - - • JC )( x + )( ++++ JI + )( x x )( + .. 7 Response of FFIFB control during nduced rate 148 147 + + )(+ )(+ )( • x x x ... - - .... - 144 143 143 142 141 ----�--�---. �-'--�------ - · - · - - - -,_-"::. :". :: :. _ . ,c 142 . 141 +-. · - · - · -· - · - ·- · - · - ·- · - · - · - ·- · - · - · - · -· - · - · - · - · -· - · - · · - - - ... ... _ · - · -· - · - - - 1 - - - ... 1'40 0 2 4 TIME r-J -- s 6 137 136 fat - - - - Exp.

It is important to stress that despite appearances, it does not involve approximat­ ing a differential with a finite difference. to = (16) 0, (16) 11 (0) = t/>ot; + t/>1z1 ( t;) + t/>2 z2 (t ;) + ")'owo( t ;) + ")'1w1 ( t ;) + -r2w2( t;) (17) where z1 (t;) = fo'; y (t) dt; z2 ( ti ) = J0'; y(t ) 2 dt; wo( t ;) = J:; u ( t) dt; w1 (ti) = J:; y(t ) u(t)dt; w2( t;) = fo'; 11(t) 2 u (t)dt The model identification problem is now as follows: given input/output data u(h), y(t1<); k = 1 , 2 , . . , N , and y (O), obtain estimates of the six model parameters using the equation: 4 EXAMPLES The Isothermal Reactor The process (cf.

_ · - · -· - · - - - 1 - - - ... 1'40 0 2 4 TIME r-J -- s 6 137 136 fat - - - - Exp. ,' '�.... " __ _ _-____-___.... _ �·�-___ X x • • ' x .... - ... - ..... _ _ _ . __ ... .... 1 u ++++ Each room Fig. 8 Response of MPC during reduced rate 32 _ • •xxxxxxxxx xx •xxxx xxxxxx + ... +-+· -+ ·+-+·-+. M. B. Brosilow. ( 1990). (3) Nonlinear Model Predictive Control of S tyrene Poly­ merization at Unstable Operating Points.

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