Supervision based on partial predictors for a multimodel generalised predictive control: experimental validation on a semi-batch reactor

Messaoud, Anis; Ltaïef, Majda; Abdennour, Ridha Ben

doi:10.1504/ijmic.2009.024740

Cited by 19 publications

(17 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The following criterion is minimal for the nearest predictor output to the system output. It has the following expression [33], [34], [35]:…”

Section: Decoupled Multimodel Predictive Control With Supervisionmentioning

confidence: 99%

Supervised Model Predictive Control for Discrete-time Nonlinear Systems with Time-varying Delay

Atia¹,

Messaoud²,

Abdennour³

2015

IJCA

Self Cite

View full text Add to dashboard Cite

The present paper deals with a decoupled multimodel predictive control based on multi-observer for the control of discrete-time nonlinear systems with time-varying delay. For each local model, a controller based on partial predictor/observer is synthesized. A switching algorithm is established to yield the adequate partial controller ensuring the closed-loop desired performances. Simulation results are given to illustrate the significance of the proposed decoupled multimodel predictive control strategy.

show abstract

“…The following criterion is minimal for the nearest predictor output to the system output. It has the following expression [33], [34], [35]:…”

Section: Decoupled Multimodel Predictive Control With Supervisionmentioning

confidence: 99%

Supervised Model Predictive Control for Discrete-time Nonlinear Systems with Time-varying Delay

Atia¹,

Messaoud²,

Abdennour³

2015

IJCA

Self Cite

View full text Add to dashboard Cite

show abstract

“…The reaction carried out in this reactor is a chemical esterification of the crude acid of olive oil by an alcohol, such as butane, in order to extract an ester with high quality. The produced ester is widely used for the manufacture of cosmetic products [5]. The esterification reaction is given as follow:…”

Section: H2w2nementioning

confidence: 99%

“…2). It is also cooled in a tubular cooler whose cooling rate is changed by varying the external water [5]. The variables Tede and Tsde are respectively input and output temperature of double envelope, Tr is the reactor's temperature and Q is the heating power.…”

Section: H2w2nementioning

confidence: 99%

“…Batch reactors are becoming more and more used according to their importance in manufacturing industries, such as chem icals and pharmaceuticals production [5], [6], [15]. Therefore, the non linearity and the uncertainty of these processes make their emulation difficult.…”

Section: Introductionmentioning

confidence: 99%

“…Because of the nonlinearity, it is hard to use conventional control techniques, based on the linearization of the system [7]. Several researchers [5], [6] are interested to solve this problem. The difficulty in establishing an accurate mathematical model can be overcome by applying a neural emulation method for the temperature control of the chemical reactor.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Neural emulation applied to chemical reactors

Atig

Druaux

Lefebvre

et al. 2010

2010 7th International Multi- Conference on Systems, Signals and Devices

Self Cite

View full text Add to dashboard Cite

In this paper, a real time recurrent learning-based emulator is presented for nonlinear plants with unknown dy namics. This emulator is based on fully connected recurrent neural networks. Starting from zero values, updating rate, time parameter and weights of the instantaneous neural emulator adapt themselves in order to estimate the process output. The contribution of this paper is to validate the emulator with experimental data from the batch reactor of National Engineering School of Gabes, Tunisia.

show abstract

Optimal Systematic Determination of Models’ Base for Multimodel Representation: Real Time Application

Ltaïef

Messaoud

Abdennour

2014

Int. J. Autom. Comput.

Self Cite

View full text Add to dashboard Cite

The multimodel approach is a powerful and practical tool to deal with analysis, modeling, observation, emulation and control of complex systems. In the modeling framework, we propose in this paper a new method for optimal systematic determination of models base for multimodel representation. This method is based on the classification of data set picked out of the considered system. The obtained cluster centers are exploited to provide the weighting functions and to deduce the corresponding dispersions and their models base. A simulation example and an experimental validation on a semi-batch reactor are presented to evaluate the effectiveness of the proposed method.

show abstract

Supervision based on partial predictors for a multimodel generalised predictive control: experimental validation on a semi-batch reactor

Cited by 19 publications

References 0 publications

Supervised Model Predictive Control for Discrete-time Nonlinear Systems with Time-varying Delay

Supervised Model Predictive Control for Discrete-time Nonlinear Systems with Time-varying Delay

Neural emulation applied to chemical reactors

Optimal Systematic Determination of Models’ Base for Multimodel Representation: Real Time Application

Contact Info

Product

Resources

About