A practical application of the interval type-2 fuzzy controller for a photovoltaic sourced DC – DC boost converter

Yatak, Meral Özarslan; Bay, Ömer Faruk

doi:10.3233/ifs-130968

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…The variable * () x  stands for the average of upper and lower firing levels. Combining (1) and ( 2), a single expression for type-reduction/defuzzification can be obtained, as shown in (3).…”

Section: Type-reduction Pwm Architecturementioning

confidence: 99%

A PWM Nie-Tan Type-Reducer Circuit for a Low-Power Interval Type-2 Fuzzy Controller

2021

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A novel Type-Reduction/Defuzzification circuit architecture for an analog interval type-2 fuzzy inference system is proposed. Based on the Nie-Tan type-reduction method, the circuit operates with current-mode inputs, representing the firing intervals of the rules created by the inference engine, and generating a PWM output. It is demonstrated that by selecting an appropriate number of consequents it is possible to create the PWM output directly, without the need for analog multiplier/divider circuits. This feature makes the circuit very simple, aiding in the design process, while the PWM output makes it suitable for controlling DC-DC converters, maximum power point trackers (MPPT) for energy generators, or other switching applications. It is designed to achieve very low power consumption, allowing its use in power restrained environments, such as energy harvesting systems. The circuit was designed using TSMC 0.18µm technology, in CADENCE Virtuoso software, and simulated for different combinations of input values, demonstrating its capabilities. It was also simulated as part of a type-2 fuzzy inference system with two inputs, nine rules, and firing intervals represented by currents within 0 and 10µA. The circuit was prototyped, and the experimental average power consumption was only 53.8µW, validating its low power consumption characteristic.

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Section: Type-reduction Pwm Architecturementioning

confidence: 99%

A PWM Nie-Tan Type-Reducer Circuit for a Low-Power Interval Type-2 Fuzzy Controller

2021

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“…In some other more works, type-2 fuzzy [36,37], swarm optimization [38] and bee colony algorithms [39] for a power electronic converter systems, respectively. They have found that both algorithms have been successful for the optimization of the above-mentioned systems.…”

Section: Ann Applications In Electrical Machinesmentioning

confidence: 99%

Artificial neural network analysis on an axial flux permanent magnet generator having variable air gap and power regime

Tekerek

Kurt

2021

Sādhanā

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In the present study, an artificial neural network (ANN) design has been proposed to analyze and estimate the output quantities of a newly manufactured generator, namely axial flux permanent magnet generator (AFPMG). The machine has been designed with a maximum power of 3 kW for the household electric power generation. As one of the innovative points, this machine has a variable air gap between the stator and the rotors, thereby the maximal power scale can be determined easily by adjusting the air gap between 2 mm and 7 mm. It means that the maximal power has values between 3 kW and 1.5 kW. ANN approach for such a machine is important in the sense that the estimation of output power, voltage and current values under various speeds and electrical loads are vital for the optimum operation of the machine. The designed ANN algorithm has been successful to estimate the output power and voltage of the newly produced generator for different air gap and speed and electrical load parameters.

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“…Bu çeviriciler doğrusal olmayan yapılarından dolayı birçok çalışmanın da odak noktası haline gelmiştir. Bu çalışmalar yeni tasarım ve dayanıklı denetim ilkelerine dayanmaktadır [4][5]. Bilindiği gibi DA-DA çevirici yapılarının çıkışlarından belirli bir seviyeye kadar gerilim değerleri elde edilebilmektedir.…”

Section: Igi̇ri̇şunclassified

Aralıklı Tip-2 Bulanık Mantık Denetleyici Tabanlı Yükselten Tip DA-DA Çevirici Yapısının Denetimi ve Deneysel Analizi

Açıkgöz¹,

Keçecioğlu

2020

Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi

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Bu çalışmada, yükselten tip DA-DA çeviricinin çıkış geriliminin denetimi için Aralıklı Tip-2 Bulanık Mantık Denetleyici (AT2BMD) yapısı önerilmiştir. Bu denetleyici yapısı ile yük değişimine karşı DA-DA çeviricinin dinamik cevabının iyileştirilmesi amaçlanmıştır. Bu amaçla ilk olarak yükselten tip DA-DA çevirici yapısı deneysel olarak geliştirilmiştir. Daha sonra önerilen denetleyici yapısının performansının ve güvenilirliğinin incelenmesi için birbirinden farklı iki deneysel çalışma durumu oluşturulmuştur. AT2BMD ile Tip-1 BMD (T1BMD) bu çalışma durumları altında karşılaştırılmıştır. Bu denetleyici yapılarının deneysel çalışmalara uygulanabilmesi için dSPACE DS1104 denetleyici kartı kullanılmıştır. Elde edilen sonuçlara göre önerilen denetleyici yapısının her iki deneysel çalışmada da T1BMD'den daha tatmin edici dinamik cevaplar sağladığı açıkça gözlenmiştir.

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A practical application of the interval type-2 fuzzy controller for a photovoltaic sourced DC – DC boost converter

Cited by 9 publications

References 17 publications

A PWM Nie-Tan Type-Reducer Circuit for a Low-Power Interval Type-2 Fuzzy Controller

A PWM Nie-Tan Type-Reducer Circuit for a Low-Power Interval Type-2 Fuzzy Controller

Artificial neural network analysis on an axial flux permanent magnet generator having variable air gap and power regime

Aralıklı Tip-2 Bulanık Mantık Denetleyici Tabanlı Yükselten Tip DA-DA Çevirici Yapısının Denetimi ve Deneysel Analizi

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