A Model Predictive Controller Using Multiple Linear Models for Continuous Stirred Tank Reactor (CSTR) and ITS Implementation Issue

Agarwal, Vivek; Gupta, Manish Kumar; Gupta, Umesh Kumar; Saraswat, Rahul

doi:10.1109/csnt.2014.204

Cited by 9 publications

(3 citation statements)

References 7 publications

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“…In ref a multimodel MPC for the component content in the CePr/Nd counter current extraction process was discussed. In ref decomposition of the nonlinear system into a series of linear models and the nonlinear MPC are discussed. Fractional order systems can improve the accuracy of process models, and improved control performance may be anticipated.…”

Section: Introductionmentioning

confidence: 99%

Multimodel Fractional Predictive Functional Control Design with Application on an Industrial Heating Furnace

Zou

Tao

et al. 2018

Ind. Eng. Chem. Res.

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This paper mainly targets the nonlinear characteristics in industrial heating furnace control and uses the multimodel method to decompose the global dynamics of the process into a series of local model sets. The corresponding predictive functional controller is designed using the local fractional order models of the set within their working range. The weight coefficients of the different models in the model sets are obtained based on the error of the different model sets at current moment, and the system performance at current moment is obtained by weighting between many models using the weight coefficient. Since the accuracy of the local models is increased, the error between the local model set and the process output is reduced, which decreases the influence of the system model inaccuracy on the system performance. Finally, the strategy is verified through the experiment on the temperature of a heating furnace.

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Section: Introductionmentioning

confidence: 99%

Multimodel Fractional Predictive Functional Control Design with Application on an Industrial Heating Furnace

Zou

Tao

et al. 2018

Ind. Eng. Chem. Res.

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“…El objetivo de este trabajo es evaluar la conveniencia de aplicar una estrategia DMPC (Distributed Model Predictive Control) analizando su robustez ante fallas en los sensores y/o actuadores del sistema. Como caso de estudio consideramos un sistema comúnmente empleado en la investigación de MPC y sus variantes, el Reactor tipo Estanque Agitado (Continuous Stirred Tank Reactor, CSTR) [3]- [6].…”

Section: Introduccionunclassified

Performance Evaluation of a Distributed MPC Strategy Applied to the Continuous Stirred Tank Reactor

Lagos

Cipriano

2015

IEEE Latin Am. Trans.

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The search of more robust solutions for multipleinput multiple-output (MIMO) process control has motivated the development of complex modeling and control techniques for such systems. In this work the performance of a distributed controller (Distributed Model Predictive Control DMPC) versus a centralized solution (Model Predictive Control, MPC) are compared when faults in sensors and actuators occur. Preliminary results show that for faults in actuators the distributed solution has a better response but it requires more calculation time.

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“…Moreover, MPC is posed as a suitable alternative to design decentralized multivariable PID controllers in applications like biodiesel reactors, where complex decoupling techniques are required, yet not completely effective [3]. Many of this works provide with evidence of the advantages of MPC in such systems using simulations [4], [5], [6] while some others moved to real-scale implementation with success [1], although few is available on dealing with the computational requirements of such implementation in average industrial control equipment. Ho et al [3] used centralized adaptive generalized predictive control (CA-GPC) to handle multiple control loops of a transesterification batch reactor, instead of using a decentralized multiple-controller strategy.…”

Section: Introductionmentioning

confidence: 99%

Temperature regulation of a pilot-scale batch reaction system via explicit model predictive control

Sanchez-Cossio

Ortega-Alvarez

Ocampo‐Martínez

2015

2015 IEEE 2nd Colombian Conference on Automatic Control (CCAC)

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Abstract-In this paper, the temperature of a pilot-scale batch reaction system is modeled towards the design of a controller based on the explicit model predictive control (EMPC) strategy. Some mathematical models are developed from experimental data to describe the system behavior. The simplest, yet reliable, model obtained is a (1,1,1)-order ARX polynomial model for which the mentioned EMPC controller has been designed. The resultant controller has a reduced mathematical complexity and, according to the successful results obtained in simulations, will be used directly on the real control system in a next stage of the entire experimental framework.

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A Model Predictive Controller Using Multiple Linear Models for Continuous Stirred Tank Reactor (CSTR) and ITS Implementation Issue

Cited by 9 publications

References 7 publications

Multimodel Fractional Predictive Functional Control Design with Application on an Industrial Heating Furnace

Multimodel Fractional Predictive Functional Control Design with Application on an Industrial Heating Furnace

Performance Evaluation of a Distributed MPC Strategy Applied to the Continuous Stirred Tank Reactor

Temperature regulation of a pilot-scale batch reaction system via explicit model predictive control

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