AIChE Symposium Series, Volume 93, Issue 316American Institute of Chemical Engineers, 1997 - Chemical engineering |
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Page 16
... factor Co so that A CoA and B = Co B. We can then write the characteristic polynomial ( 7 ) so that = Co ( RA + B'Se ) = Pe The common factor must show up in the denominator of the closed loop . An unstable common factor there- fore ...
... factor Co so that A CoA and B = Co B. We can then write the characteristic polynomial ( 7 ) so that = Co ( RA + B'Se ) = Pe The common factor must show up in the denominator of the closed loop . An unstable common factor there- fore ...
Page 150
... factor for the infeasibility norms || r1 || and || r2 || should be smaller than the reduction factor for μ ; that is , the ratios || rk || / μk and || r2 || / μ should de- crease monotonically with k ; ( ii ) The pairwise products xs ...
... factor for the infeasibility norms || r1 || and || r2 || should be smaller than the reduction factor for μ ; that is , the ratios || rk || / μk and || r2 || / μ should de- crease monotonically with k ; ( ii ) The pairwise products xs ...
Page 267
... factors kept determines the degree of fit of the data by the MVS model , as well as the sensitivity of the MVS model to small changes in the data . If enough factors are not retained , the resultant MVS model would not fit the data well ...
... factors kept determines the degree of fit of the data by the MVS model , as well as the sensitivity of the MVS model to small changes in the data . If enough factors are not retained , the resultant MVS model would not fit the data well ...
Contents
Industry Assessment | 1 |
Predictive Control | 5 |
Adaptive and Nonlinear Control Fact or Fantasy? | 9 |
Copyright | |
22 other sections not shown
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adaptive control AIChE algorithm analysis analytical applications approach auto-correlation batch behavior changes Chem Chemical Engineering chemical process chip closed-loop constraints continuous control problems control system controller design defined developed discrete disturbance dynamic equations estimation example feedback control Figure finite Grafcet horizon hybrid systems identification IEEE implementation input linear control loop manufacturing matrix measured methods model predictive control monitoring Morari multivariable neural networks nonlinear control nonlinear model nonlinear systems on-line operating optimal control output error paper machine parameters Petri net PID controllers plant Proc process control process model programming Pulp and Paper quadratic quadratic program reactor robust robust control scheduling sensors sequence set point significant simulation snack food solution specifications stability step structure synthesis TAPPI Press techniques temperature theory tion trajectory transfer function trend trol uncertainty valve variables variance vector wafer