Application of Genetic Algorithms in identification and control of a new system humidification inside a newborn incubator

Zermani, M. A.; Feki, E.; Mami, Abdelkader

doi:10.1109/ccca.2011.6031225

Cited by 15 publications

(8 citation statements)

References 6 publications

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“…In Fig. 1 we based our design on a system able to put our process in open-loop (modeling) or closed loop (control) (Zermani et al, 2011). The experimental device consists of putting the incubator in open loop which allows having a flow of air with space heater characteristics.…”

Section: Methodsmentioning

confidence: 99%

Application of Adaptive Predictive Control to a Newborn Incubator

Zermani¹

2011

American Journal of Engineering and Applied Sciences

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Problem statement: This study presents an application of Indirect Adaptive Generalized Predictive Control (IAGPC) of an incubator for newborn, in order to improve the performance of temperature control. Approach: Analysis of physical phenomena of incubator was involved together knowledge of the dynamic behavior. Incubator was identified by means of Recursive Least Square (RLS) technique associated with a projection of the model parameters for robust system identification. Results: Results showed that mathematical model of neonatal incubator predicted coincide with the measured data. A comparative study was made between ON-OFF, PID and IAGPC control in order to provide the performance of each strategy. Conclusion: Results had proved effectiveness of the IAGPC as a control of incubator system

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Section: Methodsmentioning

confidence: 99%

Application of Adaptive Predictive Control to a Newborn Incubator

Zermani¹

2011

American Journal of Engineering and Applied Sciences

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“…In [8], the same authors developed an application of Indirect Adaptive Generalized Predictive Control compared with ON-OFF and PID controller. In the same year, they designed a new active system which is able to generate the control of humidity and carried out a comparative study between GA-PID and GA-MPC [9].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Matrix Control DMC using the Tuning Procedure based on First Order Plus Dead Time for Infant-Incubator

Ali¹,

Feki²,

Mami³

2019

IJACSA

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The concept of Model Predictive Control (MPC) is considered as one of the most important controlling strategies. It is used in several fields, such as petrochemical, oil refinery, fertilizer and chemical plants. It is also well spread among the clinicians and in the biomedical fields. In this context, our paper aims to investigate the thermal conditions inside the infant incubator for premature babies. In this study, we propose the Dynamic Matrix Control (DMC) as a control strategy. The most particularity of this strategy is applicable to the Multi-input Multi-output (MIMO) systems. It aims to compare different coupled transfer functions achieved by two identification methods in previous work. Also, a simulation of the air temperature and humidity is achieved inside the unit care. In this work, we focus on the tuning controlling parameters because it is considered as a key step in the successful performance of (DMC). Then, to obtain the (DMC), we have used an analytic tool, which is the Process Reaction Curve (PRC), for higher order transfers function because it needs a lot of work for this purpose. It should be approximated as a low order transfer function with time delay, which is achieved by using the First Order Plus Dead Time (FOPDT) of processing models. Finally, the result of the comparison of the infant-incubator is provided to show an optimal and good performance of the thermal behavior of our propos methodology and prove that a good identification ensures a better performance.

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“…Also we developed a microcontroller-based system devoted to control the humidity and the heating of the newborn incubator. The system developed measures the air temperature and the humidity by tow sensors LM35 and SY-230 [12]. Then, these data were exported to a microcomputer to be analyzed.…”

Section: A Descriptionmentioning

confidence: 99%

GPC multivariable control applied to temperature and humidity neonate incubators

Zermani

Feki

Mami

2013

2013 International Conference on Electrical Engineering and Software Applications

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This paper presents a multivariable predictive control algorithm to resolve the coupling effect in closed loop systems. The desired decoupling is achieved by including an appropriate weighting factor on the objective function of predictive control. This weighting factor is tuned in synchronization to the error observation to eliminate the strong interaction. The proposed algorithm is applied to the control of humidity and temperature of a neonatal incubator. Simulation results are verified and compared with the others algorithm in the literature.

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Application of Genetic Algorithms in identification and control of a new system humidification inside a newborn incubator

Cited by 15 publications

References 6 publications

Application of Adaptive Predictive Control to a Newborn Incubator

Application of Adaptive Predictive Control to a Newborn Incubator

Dynamic Matrix Control DMC using the Tuning Procedure based on First Order Plus Dead Time for Infant-Incubator

GPC multivariable control applied to temperature and humidity neonate incubators

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