Comparison of the error-integral performance indexes in a GA-tuned PID controlling system of a PWR-type nuclear reactor point-kinetics model

Mousakazemi, Seyed Mohammad Hossein

doi:10.1016/j.pnucene.2020.103604

Cited by 43 publications

(21 citation statements)

References 20 publications

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“…To improve this result, type-2 fuzzy logic was proposed in order to improve the errors of the estimation of the variable. To have an idea about the errors dimension, the ISE was applied; the ITAE is not a good election because as the error does not converge to zero, and if it is multiplied for time, the result is too big [20]. Finally, some relative error is presented by dividing the ISE and ITAE by the maximum error obtained.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, some relative error is presented by dividing the ISE and ITAE by the maximum error obtained. The ISE is the integral of square error (27) [20]. Thus if a small error is obtained, the ISE can be small, but according to the magnitudes, a relatively small error in which magnitude is not negligible can have a large ISE that could be interpreted as a bad result.…”

Section: Resultsmentioning

confidence: 99%

“…In this case, the error criteria for phenol and biomass, using type-2 fuzzy logic, were 49.26% and 21.27% fewer, respectively. In control, issues have no importance, but the intermediate has a better approach in type-2 fuzzy logic, with an improvement of 85.79% in the ISE, and this variable can be used for control law design [20]. Errors from noise were reduced because fuzzy logic works as a filter.…”

Section: Discussionmentioning

confidence: 99%

“…It is considered a Sugeno inference system where the consequents are state-space representations, and for each state space (20), an observer is designed, the scheduling vector that contains the membership degrees, depends only on measured variables and a candidate Lyapunov = T ( ) (t) function is derived with = T .…”

Section: Fuzzy Observersmentioning

confidence: 99%

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Interval Type-2 Fuzzy Observers Applied in Biodegradation

Márquez-Vera

Rodríguez-Romero

Márquez-Vera

et al. 2021

IJRCS

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There exist processes difficult to control because of the lack of inline sensors, as occurs in biotechnology engineering. Commonly the sensor is expensive, damaged, or even they do not exist. It is important to build an observer to have an approximation of the process output to have a closed-loop control. The biotechnological processes are nonlinear, thus in this work is proposed a fuzzy observer to endure nonlinearities. To improve the results reported in the literature, type-2 fuzzy logic was used to justify the membership functions used. The observer's gains were computed via LMIs to guarantee the observer's stability. To facilitate the fuzzy inference computation, interval type-2 fuzzy sets were implemented. The results obtained with the interval type-2 fuzzy observer were compared with a similar technique that uses a fuzzy sliding mode observer; this new approach gives better results obtaining an error 60% lower than the obtained with the other technique. They were designed three observers that work ensemble via a fuzzy relation. The best approximation was to estimate the intermediate concentration. It is important to know this variable because this sub-product was also toxic. It was concluding that by using the oxygen concentration and the liquid volume inside the reactor, the other concentrations were estimated. Finally, this result helps to design a fuzzy controller by using the estimated state. Using this approach, the estimation errors for the phenol and biomass concentrations were 49.26% and 21.27% lower than by using sliding modes.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Fuzzy Observersmentioning

confidence: 99%

See 2 more Smart Citations

Interval Type-2 Fuzzy Observers Applied in Biodegradation

Márquez-Vera

Rodríguez-Romero

Márquez-Vera

et al. 2021

IJRCS

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“…PID control’s commonly used error integral objective functions include integral of squared error criterion (ISE), integral of time multiplied by squared error criterion (ITSE), integral of absolute value error criterion (IAE), and integral of time multiplied by the absolute value of error criterion (ITAE). 27 This article proposes an improved objective function based on ITAE for the SOPDT process as the fitness function of the PSO TDF-IMC-PID algorithm (PSO-TDF-IMC-PID). The ITAE expression is as follows…”

Section: Algorithm and Controller Designmentioning

confidence: 99%

Two-degree-of-freedom internal model control of particle swarm optimization for flow temperature control system in phase change material packaging technology

Zhang

Duan

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this article, a phase change material packaging process system was designed. In view of the hysteresis of the system flow temperature control, a two-degree-of-freedom internal model PID (PSO-TDF-IMC-PID) controller based on particle swarm optimization was determined based on the flow regulating valve model, so as to control the phase change material outlet temperature to keep constant with establishing the system heat transfer model. Compared with other control algorithms, the PSO-TDF-IMC-PID algorithm is proved to be fast, anti-interference and robust. The traditional integral of time multiplied by the absolute value of error criterion performance index is improved, and the improved integral of time multiplied by the absolute value of error criterion is applied to PSO-TDF-IMC-PID algorithm for simulation comparison. Simulation results show that the improved integral of time multiplied by the absolute value of error criterion can effectively eliminate overshoot. The overshoot is reduced from the original 8% to almost 0. To reduce system energy consumption and improve economy, energy consumption constraint conditions are added into the variable trial-error algorithm to calculate economic flow rate and inlet temperature of heat conduction oil. The results show that the dynamic parameters of the system accord with the constraint condition of energy consumption.

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