Combined ANFIS method with FA, PSO, and ICA as Steering Control Optimization on Electric Car

Ali, Machrus; Muhlasin,; Nurohmah, Hidayatul; Raikhani, Agus; Sopian, Hendi; Sutantra, Nyoman

doi:10.1109/eeccis.2018.8692885

Cited by 17 publications

(12 citation statements)

References 11 publications

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“…The FA parameter data in Table 1 is used as a parameter of the program's FA parameters [19]. For example, the design PID Controller for Dual-axis simulation is shown in Figure 2.…”

Section: Modelingmentioning

confidence: 99%

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Ali

Suyono²,

Muslim³

et al. 2022

Sinergi

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The optimal performance of solar panels is very important to produce maximum electrical energy. Solar panels can work optimally when equipped with a solar tracker. The solar panel tracker works by following the sun's movement. A Proportional, Integral, Derivative (PID) based control is used to optimize the performance of the solar tracker. An optimal tuning is needed to get the PID parameter. The Firefly method is an intelligent method that can be used to optimize PID parameters. Three Firefly Algorithm (FA) parameters are used in the program: Beta is used to determine firefly speed, Alpha is used for flexibility of movement, and Gamma is used for more complex constraints or problems. This Dual Axis photovoltaic tracking study uses the beta value determination, changing the Bêta value from 0.1 to 0.9. From the results of 10 models, it was found that the PID constant values were varied. On the horizontal Axis, the best results are if the Beta is given at 0.4, and the worst result is if the Beta is given at 0.8. On the vertical Axis, the best results are if the Beta is given at 0.3, and the worst result is if the Beta is given at 0.8.

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“…The FA parameter data in Table 1 is used as a parameter of the program's FA parameters [19]. For example, the design PID Controller for Dual-axis simulation is shown in Figure 2.…”

Section: Modelingmentioning

confidence: 99%

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Ali

Suyono²,

Muslim³

et al. 2022

Sinergi

Self Cite

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“…Dalam simulasi, arsitektur ANFIS digunakan untuk memodelkan fungsi nonlinier, mengidentifikasi komponen nonlinier secara online dalam sistem kontrol [26]. Ukuran divalidasi dengan membandingkan model CARSIM yang diusulkan, yang merupakan perangkat lunak yang divalidasi secara eksperimental [27]. FIS yang digunakan adalah model fuzzy tingkat pertama dari model Tagaki-Sugeno-Kang (TSK) dengan pertimbangan kesederhanaan dan kemudahan komputasi [26][18].…”

Section: Adaptive Neuro-fuzzy Inference System (Anfis)unclassified

Komparasi PID, FLC, dan ANFIS sebagai Kontroller Dual Axis Tracking Photovoltaic berbasis Bat Algorithm

Nurohmah

Ali

Rukslin

et al. 2022

jeetech

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Photovoltaic merupakan pembangkit energy listrik terbarukan yang sangat cocok untuk negara trapis yang banyak mendapat sinar matahari. Akan tetapi pembangkit ini mempunyai efisiensi yang masih kecil. Untuk mengatasi kekurangan ini, beberapa peneliti telah megoptimasi dengan metode dual axis tracking solar secara konvensional. Diperlukan penelitian dengan mengoptimasi menggunakan kecerdasan buatan, dalam hal ini Adaptive Neuro-Fuzzy Inference System (ANFIS) dan Bat Algorithm (BA). Dengan membandingkan performasi model tanpa kontrol, model PID konvensional, PID Auto tuning matlab, metode Fuzzy Logic Controller (FLC), metode ANFIS, dan metode ANFIS-BA. Hasil simulasi menunjukkan bahwa desain model terbaik pada harisontal axis dan vertical axis dual tracking photovoltaic adalah ANFIS-BA dengan overshot terkecil, undershot terkecil, dan settling time tercepat dari semua desain model.

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“…The idea behind PSO is each particle keeps track of the coordinates in the space of the problem which is associated with the best solution [20]. Many studies have combined PSO with fuzzy and ANFIS in different applications [21][22][23][24][25]. In most of them the PSO tries to optimize the ANFIS parameters to give the best solutions.…”

Section: Combined Pso With Anfis To Reject the Bias Disturbancementioning

confidence: 99%

Application of particle swarm optimization with ANFIS model for double scroll chaotic system

Wali

2021

IJECE

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The predictions for the original chaos patterns can be used to correct the distorted chaos pattern which has changed due to any changes whether from undesired disturbance or additional information which can hide under chaos pattern. This information can be recovered when the original chaos pattern is predicted. But unpredictability is most features of chaos, and time series prediction can be used based on the collection of past observations of a variable and analysis it to obtain the underlying relationships and then extrapolate future time series. The additional information often prunes away by several techniques. This paper shows how the chaotic time series prediction is difficult and distort even if Neuro-Fuzzy such as Adaptive Neural Fuzzy Inference System (ANFIS) is used under any disturbance. The paper combined particle swarm (PSO) and (ANFIS) to exam the prediction model and predict the original chaos patterns which comes from the double scroll circuit. Changes in the bias of the nonlinear resistor were used as a disturbance. The predicted chaotic data is compared with data from the chaotic circuit.

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Combined ANFIS method with FA, PSO, and ICA as Steering Control Optimization on Electric Car

Cited by 17 publications

References 11 publications

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Determination of the parameters of the firefly method for PID parameters in solar panel applications

Komparasi PID, FLC, dan ANFIS sebagai Kontroller Dual Axis Tracking Photovoltaic berbasis Bat Algorithm

Application of particle swarm optimization with ANFIS model for double scroll chaotic system

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