## AIChE Symposium Series, Volume 93, Issue 316American Institute of Chemical Engineers, 1997 - Chemical engineering |

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Page 12

Towards this end we define the linear controller robustness requirements . We

call the model corresponding to this

comparing equations ( 1 ) and ( 2 ) we define the additive , unstructured

mismatch so that ...

Towards this end we define the linear controller robustness requirements . We

call the model corresponding to this

**parameter**for the centered model . Bycomparing equations ( 1 ) and ( 2 ) we define the additive , unstructured

mismatch so that ...

Page 159

The updated

encounters a constraint , the situation should be ... Key design decisions for

model updating include measurements used ,

The updated

**parameters**can be constrained in Problem 1 , but if a**parameter**encounters a constraint , the situation should be ... Key design decisions for

model updating include measurements used ,

**parameters**updated , and the**parameter**...Page 211

Robust / Adaptive Control of Systems with Time - Correlated

Uncertainty Assume that 0 evolves according to the following equation : Ok + 1 =

Ok + Ek ( 68 ) Robust Control of Systems with Time - Indepent

Uncertainty Let ...

Robust / Adaptive Control of Systems with Time - Correlated

**Parameter**Uncertainty Assume that 0 evolves according to the following equation : Ok + 1 =

Ok + Ek ( 68 ) Robust Control of Systems with Time - Indepent

**Parameter**Uncertainty Let ...

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### Contents

Industry Assessment | 1 |

Predictive Control | 5 |

Adaptive and Nonlinear Control Fact or Fantasy? | 9 |

Copyright | |

23 other sections not shown

### Common terms and phrases

achieve adaptive control addition algorithm analysis applications approach associated batch behavior bounded changes chemical closed complex Conference consider constant constraints continuous control system defined described determine developed direction discrete discussed disturbance dynamic effective engineering equations error estimation example exist factor Figure function future given horizon hybrid systems identification IEEE implementation important improved increase industrial initial input issues limited linear loop machine manufacturing matrix measurement methods monitoring networks nonlinear nonlinear control objective obtained on-line operating optimization output parameter performance plant possible practice present problem process control programming properties Pulp reactor represent respect response robust scheduling set point setpoint shown shows significant simulation solution solved specifications stability step structure techniques temperature theory tion transition trend uncertainty variables vector wafer