A design of switching supervisory control based on fuzzy-PID controllers for VVER-1000 pressurizer system with RELAP5 and MATLAB coupling

Lotfi, Mohammad Reza; Menhaj, Mohammad Bagher; Hosseini, Seyed Ali; Shirani, Amir Saeed

doi:10.1016/j.anucene.2020.107625

Cited by 17 publications

(6 citation statements)

References 13 publications

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“…Here, the first part of the temperature profile for the period 0≤t ≤ 100 seconds repersent steady operation regime while the second part accounts for when the FCC plant experiences unmeasured disturbance. In both set point tracking and disturbance rejection, the fuzzy-PID controller offers good promise of improving unit performance as deduced from the figure 10 through 12.Although the fields of application are different, the results from this study are in tandem with the contexts and arguments presented in Valayudhaan [19],Van et al [20] Mohammad et al [21] and Hema 3 further show the superior performnance of the Fuzzy-PID control scheme in the light of regenerator temperature tracking over the classical PID controller and they are inportant to process safety and operation.For instance, a regenerator temperature oversoot of 12.6% that is unattended to for 80 seconds is capable of causing undesirable temperature fields in the vessel,with unintended consequences such has damage to regenemerator wall refractory, unit shut down and production loss.…”

Section: Rggenerator Temperature Profilessupporting

confidence: 61%

“…Hence,insights gained from figures 6,7,8 and figure 9 are important contributions to knowledge in achieving the goal of enhanced operations of the FCCU. Although the fields of applications a, the insights and the scenarios differ from this study, similar sentiments and results in favour of the fuzzy logic controller and its variants are alluded to in Dey et al [2],El-Samahy et al [3],Vrecko [6],Ahmad et al [10],Demidova [11],Jalali [13],Veleyudhaan [19] and Lotfi et al [21]…”

Section: Riser Temperature Profilessupporting

confidence: 60%

supporting

confidence: 58%

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Synthesis and Soft Implementation of Supervisory Control Scheme in an Industrial Fluid Catalytic Cracking (FCC) Unit of a Nigerian Refinery

Josiah,

Otaraku,

Evbuomwan

et al. 2023

GJPACR

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In this paper, a self-tuning hierarchical controller in which a Fuzzy logic controller supervises the control actions of a conventional PID has been proposed, implemented and presented. The controller has been applied to a control study of Fluid Catalytic Cracking (FCC) unit riser temperature, and regenerator temperature respectively. Performance comparison of the proposed Fuzzy-PID controller and the conventional PID was made in simulation studies of regulatory and servo performances of the two controller types. Six performance measures: Percent overshoot (OS), settling time (ST), integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE) and integral time square error (ITSE) were employed as the tools for performance comparison between the conventional PID and the Fuzzy-PID controller. For the tracking of riser temperature with a set point at 524oC, the performance indicators under PID control gave the following results overshoot (14.5%); settling time (40 seconds) Integral absolute error (8.246), integral square error (3.3); integral time absolute error(1762);integral time square error (43.77) while for the same indicators under Fuzzy-PID control the following values: overshoot (3.3%); settling time (40 seconds) ;Integral absolute error (8.811); integral square error (14.5); integral time absolute error(280),;integral time square error (31.11) .The results allude to the superiority of the fuzzy-PID scheme over the PID scheme in tracking the optimal set point of riser temperature. More so, for tracking the regenerator set point temperature of 746oC, comparative study of step response under the two schemes gave the following results in six performance indicators: overshoot (PID(12.6%)/Fuzzy-PID(6%)); settling time (PID(80 seconds)/Fuzzy-PID(20seconds));Integral absolute error(PID(14.29)/Fuzzy-PID(8.63)); integral square error(PID(6.713).Fuzzy-PID(4.506)); integral time absolute error(PID(2858)/Fuzzy-PID(305.9)), integral time square error (PID(77.55)/Fuzzy-PID(33.05)).Moreover, the fuzzy-PID controller also showed superior performance over the conventional PID controller in terms disturbance rejection (regulatory response) of both riser and regenerator temperature. The results from this study suggest that the application of fuzzy-PID scheme to temperature control offers good promise of improved fluid catalytic cracking unit (FCCU) operations.

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Section: Rggenerator Temperature Profilessupporting

confidence: 61%

Section: Riser Temperature Profilessupporting

confidence: 60%

supporting

confidence: 58%

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Synthesis and Soft Implementation of Supervisory Control Scheme in an Industrial Fluid Catalytic Cracking (FCC) Unit of a Nigerian Refinery

Josiah,

Otaraku,

Evbuomwan

et al. 2023

GJPACR

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show abstract

“…Hence,insights gained from Figures 6,7,8 and 9 are important contributions to knowledge in achieving the goal of enhanced operations of the FCCU. Although the fields of applications a, the insights and the scenarios differ from this study, similar sentiments and results in favour of the fuzzy logic controller and its variants are alluded to in Dey and Ayyagan [2], El-Samahy ans Shamseldin [3],Vrecko [6], Ahmad et al [10], Demidova et al [11], Jalali et al [13], Veleyudhaan [23] and Lotfi et al [24].…”

Section: Riser Temperature Profilessupporting

confidence: 53%

Servo and Regulatory Response of an Industrial Fluid Catalytic Cracking (FCC) Unit under Fuzzy Logic Supervisory Control

Josiah

Otaraku

Evbuomwan

2023

ETJ

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“…Among them, the fuzzy control algorithm is widely used in various control systems because it has the advantage of not needing to master the mathematical model of the controlled object but organizes the control decision table according to manual rules and then determines the size of the control amount. Fuzzy control has developed rapidly, and many experts and scholars have applied it in many aspects [23][24][25][26]. However, the establishment of fuzzy mathematics requires a great deal of control experience and has greater subjectivity.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Neural Network PID Algorithm for BLDCM Speed Control System

Yin

Wang

et al. 2021

Mathematics

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Because of its simple structure, high efficiency, low noise, and high reliability, the brushless direct current motor (BLDCM) has an irreplaceable role compared with other types of motors in many aspects. The traditional proportional integral derivative (PID) control algorithm has been widely used in practical engineering because of its simple structure and convenient adjustment, but it has many shortcomings in control accuracy and other aspects. Therefore, in this paper, a fuzzy single neuron neural network (FSNNN) PID algorithm based on an automatic speed regulator (ASR) is designed and applied to a BLDCM control system. This paper introduces a BLDCM mathematical model and its control system and designs an FSNNN PID algorithm that takes speed deviation e at different sampling times as inputs of a neural network to adjust the PID parameters, and then it uses a fuzzy system to adjust gain K of the neural network. In addition, the frequency domain stability of a double closed loop PID control system is analyzed, and the control effect of traditional PID, fuzzy PID, and FSNNN PID algorithms are compared by setting different reference speeds, as well as the change rules of three-phase current, back electromotive force (EMF), electromagnetic torque, and rotor angle position. Finally, results show that a motor controlled by the FSNNN PID algorithm has certain superiority compared with traditional PID and fuzzy PID algorithms and also has better control effects.

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A design of switching supervisory control based on fuzzy-PID controllers for VVER-1000 pressurizer system with RELAP5 and MATLAB coupling

Cited by 17 publications

References 13 publications

Synthesis and Soft Implementation of Supervisory Control Scheme in an Industrial Fluid Catalytic Cracking (FCC) Unit of a Nigerian Refinery

Synthesis and Soft Implementation of Supervisory Control Scheme in an Industrial Fluid Catalytic Cracking (FCC) Unit of a Nigerian Refinery

Servo and Regulatory Response of an Industrial Fluid Catalytic Cracking (FCC) Unit under Fuzzy Logic Supervisory Control

Adaptive Fuzzy Neural Network PID Algorithm for BLDCM Speed Control System

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