Advanced Control of a Steam Generator

Andone, Daniela; Făgărăşan, Ioana; Dobrescu, Matei

doi:10.1109/is.2006.348442

Cited by 5 publications

(2 citation statements)

References 6 publications

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“…In such a model, the cause-effect relationship between control u and output y at the sampling time n is established in a discrete time representation. Each fuzzy implication is generated based on a system step response [3,4,10].…”

Section: Fuzzy Modelmentioning

confidence: 99%

Evolved Fuzzy Control System for a Steam Generator

Hossu¹,

Făgărăşan²,

Hossu³

et al. 2010

INT J COMPUT COMMUN

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Abstract:Poor control of steam generator water level is the main cause of unexpected shutdowns in nuclear power plants. Particularly at low powers, it is a difficult task due to shrink and swell phenomena and flow measurement errors. In addition, the steam generator is a highly complex, nonlinear and time-varying system and its parameters vary with operating conditions. Therefore, there is a need to systematically investigate the problem of controlling the water level in the steam generator in order to prevent such costly reactor shutdowns. The objective of this paper is to design, evaluate and implement a water level controller for steam generators based on a fuzzy model predictive control approach. An original concept of modular evolved control system, seamless and with gradual integration into the existent control system is proposed as base of implementation of the presented system.

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Section: Fuzzy Modelmentioning

confidence: 99%

Evolved Fuzzy Control System for a Steam Generator

Hossu¹,

Făgărăşan²,

Hossu³

et al. 2010

INT J COMPUT COMMUN

View full text Add to dashboard Cite

show abstract

“…Many of the papers sited in the literature also focus on the mitigation of the swell/shrinkage problems due to presence of two-phase mixtures in the Steam Drum (SD) either using elaborate mathematical models or by using fuzzy controllers [31]- [34]. The other types of papers emphasize on using advanced process control techniques [35], [36] such as Predictive control [37]- [44], Multiple Input Multiple Output (MIMO) [45] and Neural Networks [46]. Some of the literature also focuses on the accurate prediction of the level in the SD and the process dynamics.…”

mentioning

confidence: 99%