Internal Model Control Based on GANN for a Temperature Control Electrical Furnace

Kebir, Abdelkader El; Belhadj, Hamdi; Chaker, Abdelkader; Negadi, Karim

doi:10.15866/iremos.v7i5.4488

Cited by 2 publications

(10 citation statements)

References 4 publications

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“…The sensor and instrumentation amplifier set is supposed to be linear in the furnace temperature range. As reported in [1]- [3].…”

Section: Research Methods 21 Furnace System Modelssupporting

confidence: 65%

“…The mathematical modeling of electrical furnace and the model parameters of the furnace. According [1]- [3]. The electric furnace behaves like a first order process with a time constant close to 500 seconds.…”

Section: Research Methods 21 Furnace System Modelsmentioning

confidence: 99%

“…The mathematical model of electric resistance furnace is being represented in the state space as reported in [1]- [3]:…”

Section: Discrete State Representation Of the Electrical Furnace Resistancementioning

confidence: 99%

“…Knowledge of the thermal behavior of resistance furnaces is the most well-known and widespread industrial electro thermal equipment. Controlling the electric resistance furnace is a key point [1]- [11]. Most electric resistances furnaces use a thermocouple as a temperature sensor for the controller.…”

Section: Introductionmentioning

confidence: 99%

“…Are becoming increasingly complex. For resolving complicated problems measuring temperature for electric resistance furnace [1]- [4]. Thus, variables that are not directly measurable can be reconstructed from the algorithm Kalman stochastic reconstructor (KSR).…”

Section: Introductionmentioning

confidence: 99%

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Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

Kada

Kebir²,

Berka³

et al. 2021

IJEECS

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<span>Electric <span>resistance furnaces are the most popular and widely used industrial electro thermal equipment which continues to be the subject of many improvements. The aim of this paper is to control the temperature of electrical furnace for noisy thermocouple sensors. It can be assessed by observing some variables, which are very difficult to observe. Due to limitations, mainly the location of thermal sensors and their noises. In this case, the temperature measurement is trained with centered Gaussian white noise. The problem of accurate temperatures estimation for such sensors is solved using Kalman filter, which is an optimized estimator that provides a computationally efficient way to estimate system state. Thus, variables that are not directly measurable can be reconstructed from the algorithm. Kalman stochastic reconstructor (KSR). We cannot use with fixed parameters to control the temperature. For this reason, this paper comes up with a KSR approach based pole placement (PL) hybrid controller to realize an algorithm for the temperature control electrical furnace. Results based on Matlab simulation show that the improved algorithm has well produced an optimal estimate of the temperature. Evolving over time from noisy measurements. Hybrid algorithm KSR approach based PL give good performance compared to PL controllers.</span></span>

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“…The sensor and instrumentation amplifier set is supposed to be linear in the furnace temperature range. As reported in [1]- [3].…”

Section: Research Methods 21 Furnace System Modelssupporting

confidence: 65%

Section: Research Methods 21 Furnace System Modelsmentioning

confidence: 99%

“…The mathematical model of electric resistance furnace is being represented in the state space as reported in [1]- [3]:…”

Section: Discrete State Representation Of the Electrical Furnace Resistancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

Kada

Kebir²,

Berka³

et al. 2021

IJEECS

Self Cite

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A Practical Review on the Application of Constraint Handling Strategies in Evolutionary Computation from an Engineering Point of View

Yousefi

Hooshyar

Ahmad

et al. 2015

IREMOS

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This study presents a review of the current constraint handling strategies that are being employed in evolutionary computation. The strategies can be as simple as a reject strategy or as sophisticated as decoding or multi-objective approaches. In this study, however, only the prominent methods and previous works are considered. The Evolutionary algorithms cannot handle the constraints by themselves, and the growing application of EAs in various fields of engineering and science, which are mostly highly constrained, has made the use of efficient, easyto-implement and comprehensive constraint handling strategies inevitable. This study will shed light on this field of research and a comparison of various strategies will be also provided.

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Internal Model Control Based on GANN for a Temperature Control Electrical Furnace

Cited by 2 publications

References 4 publications

Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

Study of designing regulator for temperature electrical resistance furnace using Kalman stochastic reconstructor

A Practical Review on the Application of Constraint Handling Strategies in Evolutionary Computation from an Engineering Point of View

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