A kind of output-feedback networked control system was addressed to overcome the defect of feedback lag introduced by the network usage in the networked control system. By introducing a plant model and a buffer into t...
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A kind of output-feedback networked control system was addressed to overcome the defect of feedback lag introduced by the network usage in the networked control system. By introducing a plant model and a buffer into this system, when feedback was available, this system could compute the control output and update the plant model with the plant output, otherwise, compute the control output based on the plant model output instead of plant output. On the condition that the plant was SISO and the error between plant and model existed, the necessary and sufficient condition for closed-loop stability of this system was derived. Simulation indicates that the range of model error within which this system is stable is easy to be derived by using this necessary and sufficient condition.
A new kinetic model for commercial unit of toluene disproportionation and C9-armatiocs transalkylation is developed based on the reported reaction scheme.A time based catalyst deactivation function taking weight hourl...
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A new kinetic model for commercial unit of toluene disproportionation and C9-armatiocs transalkylation is developed based on the reported reaction scheme.A time based catalyst deactivation function taking weight hourly space velocity(WHSV)into account is incorporated into the model,which reasonably accounts for the loss in activity because of coke deposition on the surface of catalyst during long-term *** kinetic parameters are benchmarked with several sets of balanced plant data and estimated by the differential variable metric optimiza- tion *** of plant data at different operating conditions are applied to make sure validation of the model and the results show a good agreement between the model predictions and plant *** simulation analysis of key variables such as temperature and WHSV affecting process performance is discussed in detail,giv- ing the guidance to select suitable operating conditions.
A Neural Network Model is developed for a Kraft digester which is a fundamental stage in the pulp production. A deterministic model is used to describe the main features of the process and will provide the data to ver...
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A Neural Network Model is developed for a Kraft digester which is a fundamental stage in the pulp production. A detenninistic model is used to describe the main features of the process and will provide the data to ver...
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A Neural Network Model is developed for a Kraft digester which is a fundamental stage in the pulp production. A detenninistic model is used to describe the main features of the process and will provide the data to verify the performance of the artificial neural network modeling. The paper shows that the artificial neural network is a good way to represent the process since it gives equivalent results when compared to deterministic model, and it is easier and cheaper to be developed.
This work presents a procedure for the development of soft sensors for the concentration control of a fixed bed catalytic reactor, through the definition of the best setpoints for the temperature profile in the reacto...
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This work presents a procedure for the development of soft sensors for the concentration control of a fixed bed catalytic reactor, through the definition of the best setpoints for the temperature profile in the reactor, obtained through a optimization procedure where the process is represented by a neural network. This procedure is coupled to a multivariable control strategy based on neural networks and it acts on the temperature of the system. The objective is to control the output concentration of the reactor.
Developing fully mechanistic models for bioprocess is expensive and time-consuming. On the other hand, using pure ‘black-box’ approaches can lead to a misuse of available information, because there are aspects of th...
Developing fully mechanistic models for bioprocess is expensive and time-consuming. On the other hand, using pure ‘black-box’ approaches can lead to a misuse of available information, because there are aspects of the process that can be accurately described by simple equations as, for example, mass balances. This work analyses the use of different types of ‘black-box’ and hybrid models to outline the dynamics of a batch beer production. The hybrid models, combine mechanistic equations with ‘black-box’ techniques (reserved only for the unclear parts of the system), in order to achieve an efficient use of the available information. The hybrid models can also be called ‘grey-box’ approaches. To generate the hybrid models, different level of information is introduced into the ‘black-box’ models, allowing for an interesting model performance comparison in the end. Results demonstrate that the ‘black-box’ models present a good performance in the range of process conditions used to develop them. However, the inclusion of mechanistic knowledge into the hybrid models increase the model extrapolative capability. In this work, artificial neural networks (ANN) are used as the main technique for both the ‘black-box’ models and the ‘black-box’ parts in the hybrid models.
作者：
BULL, DNDaniel N. Bull
Ph.D. is a consultant in fermentation technology and president of Satori Corporation P.O. Box 1730 Montclair N.J. 07042. (201) 783-9787.REFERENCES Graff G.M. Short H. and Keene J.1983. Gene-splicing methods move from lab to plant. Chem. Eng.90: 22-27.|ISI|Broda P.1979. p. 1-3. Plasmids. W. H. Freeman Oxford and San Francisco.Donoghue D.J. and Sharp P.A.1978. Construction of a hybrid bacteriophage-plasmid recombinant DNA vector. J. Bact.136: 1192-1196.|PubMed|ISI|ChemPort|Bok S.H. Hoppe D. Mueller D.C. and Lee S.E.1983. Improving the production of recombinant DNA proteins through fermentation development. Abstract from 186th ACS Natl. Mtg. Washington D.C. Sept. 1.Maniatis T. Fritsch E.F. and Sam-brook J.1982. p. 88. Molecular Cloning. Cold Spring Harbor Laboratory. Guidelines for research involving recombinant DNA molecules June 1983
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