AIChE Symposium Series, Volume 93, Issue 316American Institute of Chemical Engineers, 1997 - Chemical engineering |
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Page 21
... algorithm then stops when the prediction error is small and the parameters will not drift . Algorithms based on fault detection can be ap- plied as long as the deadzone does not become too large ( Hagglund , 1983 ; Ortega and Garcia ...
... algorithm then stops when the prediction error is small and the parameters will not drift . Algorithms based on fault detection can be ap- plied as long as the deadzone does not become too large ( Hagglund , 1983 ; Ortega and Garcia ...
Page 236
... algorithm was modified to han- dle nonlinearities and constraints . Neither paper discussed their process identification technology . Key features of the DMC control algorithm include : ⚫ linear step response model for the plant ...
... algorithm was modified to han- dle nonlinearities and constraints . Neither paper discussed their process identification technology . Key features of the DMC control algorithm include : ⚫ linear step response model for the plant ...
Page 237
... algorithm as a Quadratic Program ( QP ) in which input and output constraints appear explicitly . Cutler et al . first described the QDMC algorithm in a 1983 AIChE confer- ence paper ( Cutler , Morshedi and Haydel , 1983 ) . García and ...
... algorithm as a Quadratic Program ( QP ) in which input and output constraints appear explicitly . Cutler et al . first described the QDMC algorithm in a 1983 AIChE confer- ence paper ( Cutler , Morshedi and Haydel , 1983 ) . García and ...
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