Power Optimization of Three Dimensional Turbo Code Using a Novel Modified Symbiotic Organism Search (MSOS) Algorithm

Banerjee, Subhabrata; Chattopadhyay, Sudipta

doi:10.1007/s11277-016-3586-0

Cited by 22 publications

(8 citation statements)

References 29 publications

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“…SOS algoritması doğada en yaygın biçimde görülen üç simbiyotik ilişkiden yararlanılarak geliştirilmiştir. Bu ilişkiler sırasıyla mutualizm, kommensalizm ve parazitizmdir [22]. Her bir faz organizmanın hareketini ve başka bir organizmanın yerine geçip geçmeyeceğine karar verir.…”

Section: Si̇mbi̇yoti̇k Organi̇zmalar Arama Algori̇tmasi (Symbiotic Organisms Search Algorithm)unclassified

Doğru Akım Motor Sürücüleri için PI Parametrelerinin Simbiyotik Organizmalar Arama Algoritması ile Optimal Ayarı

Çelik¹,

Öztürk²

2017

Bilişim Teknolojileri Dergisi

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Özet-Doğru akım (DA) motorları ekonomik olmaları yanında denetimlerinin basitliği ve iyi derecedeki moment-hız karakteristiklerinden dolayı hem endüstriyel uygulamaların hem de günlük yaşantımızın önemli elektrik makinalarıdır. Denetimlerinde kullanılan oransal+integral (PI) denetleyici parametrelerin doğru bir şekilde ayarı zor olmakla beraber sistemin performansı ve kararlılığı açısından önemli bir yer tutmaktadır. Bu çalışmada PI katsayılarının optimizasyonu için dayanıklı ve güçlü simbiyotik organizmalar arama (SOS) algoritmasına dayalı yeni bir alternatif çözüm sunulmaktadır. Çalışmada genetik algoritma (GA) ile klasik Ziegler-Nichols (Z-N) yöntemi kullanılarak elde edilen cevapların geçici durum analizleri yapılarak sistemin yükselme zamanı, yerleşme zamanı ve maksimum aşım değerleri karşılaştırılmıştır. Aynı zamanda ortaya konulan yaklaşımın değişik parametre durumunda gürbüzlük analizi gerçekleştirilmiştir. Gerçek bir endüstriyel motora ait parametreler ile C dili kullanılarak gerçekleştirilen benzetim sonuçlarına göre, SOS'un GA'ya göre maksimum aşım bakımından %2,1, yerleşme zamanı açısından ise GA'ya göre %25, Z-N'e göre de %73 daha iyi performansa sahip olduğu anlaşılmıştır. Öte yandan, GA ile SOS'un yükselme zamanlarının birbirine eşit olduğu, bu sonucun ise Z-N'e göre %42,9 daha iyi olduğu gözlemlenmiştir. Gürbüzlük testinde nominal değerlerden ortalama sapma miktarının %18,2 olarak hesaplanması, SOS tabanlı PI denetleyicinin gürbüz olduğunu göstermiş ve belirlenen aralıktaki değişik parametre durumundan çok fazla etkilenmeden istenen denetim davranışını sağladığı görülmüştür. Sonuç olarak sürme sisteminin referans hız izleme performansı ile bozucu etkenlere karşı dayanıklılığı artırılmıştır.Anahtar Kelimeler-DA motoru, PI denetleyici, simbiyotik organizmalar arama algoritması, genetik algoritma, ziegler-nichols, optimizasyon Optimal Setting of PI Parameters for Direct Current Motor Drives by Symbiotic Organisms Search AlgorithmAbstract-Owing to their simple control and good torque-speed characteristics in addition to being economical, direct current (DC) motors are important electric machines for both industrial applications and our daily life. Proper parameter setting of proportional+integral (PI) controller used in their control is difficult, as well as holding a strong part for performance and stability of the system. In this study, a new alternative solution based on the robust and powerful symbiotic organisms search (SOS) algorithm is presented for optimization of PI coefficients. Using genetic algorithm (GA) and classical Ziegler-Nichols (Z-N), results following the transient analysis of the obtained responses are compared in terms of rise time, settling time, and maximum overshoot. Moreover, robustness analysis of presented approach is carried out under parameter change. According to obtained simulation results realized by using C language and real industrial motor parameters, it is inferred that SOS has better performance than GA by 2,1% for maximum overshoot, and by 25% and 73% than GA an...

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Section: Si̇mbi̇yoti̇k Organi̇zmalar Arama Algori̇tmasi (Symbiotic Organisms Search Algorithm)unclassified

Doğru Akım Motor Sürücüleri için PI Parametrelerinin Simbiyotik Organizmalar Arama Algoritması ile Optimal Ayarı

Çelik¹,

Öztürk²

2017

Bilişim Teknolojileri Dergisi

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“…In Duman and Dosoglu et al, SOS has been applied to solve the optimal power flow and the economic emission load dispatch problems. Moreover, SOS has been successfully applied in the design of linear antenna arrays, in solving the load frequency control problem, in structure optimization problems, in solving unconstrained function optimization, and in the design of an improved 3D turbo code . The results indicated that SOS gives very good results and is very competitive with the state of the art for the solution of these problems, which motivated this work.…”

Section: Introductionmentioning

confidence: 98%

Optimal design of analog active filters using symbiotic organisms search

Dib

El-Asir

2018

Int J Numerical Modelling

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This paper investigates the optimal design of analog active filters using the symbiotic organisms search (SOS) algorithm. Symbiotic organisms search is a newly proposed global optimization method that is inspired by the symbiotic interaction strategies between different organisms in an ecosystem. In SOS, the 3 common types of symbiotic relationships (mutualism, commensalism, and parasitism) are modeled using simple expressions, which are used to find the global minimum of the fitness function. Unlike other methods, SOS is free of tuning parameters, which makes it an attractive optimization method. Here, SOS is used to determine the values of the passive components (resistors and capacitors) used in active filters. Two active filter topologies, fourth‐order Butterworth low‐pass filter and second‐order state variable low‐pass filter, are considered. The components values are chosen from several standard industrial series (E12, E24, and E96). The results obtained using SOS are compared with those obtained using several optimization methods, like particle swarm optimization, seeker optimization algorithm, differential evolution, and other ones. It is shown that the SOS is a robust straightforward evolutionary algorithm that can outperform other well‐known methods.

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“…In [10,11], SOS has been applied to solve the optimal power flow and the economic emission load dispatch problems. Moreover, SOS has been successfully applied in the optimal design of linear and circular antenna arrays [12,13], in solving the load frequency control problem [14], in structure optimization problems [15], in solving unconstrained function optimization [16], in the design of an improved 3D Turbo Code [17], in the optimal design of analog active filters [18], in the synthesis of elliptical antenna arrays [19], and other engineering areas [20][21][22][23][24]. The results indicated that SOS gives very good results and is very competitive with the state of the art for the solution of these problems, which motivated this work.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of symmetric switching CMOS inverter using symbiotic organisms search algorithm

Dib¹,

Al-Sammarraie²

2020

IJECE

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This paper investigates the optimal design of symmetric switching CMOS inverter using the Symbiotic Organisms Search (SOS) algorithm. SOS has been recently proposed as an effective evolutionary global optimization method that is inspired by the symbiotic interaction strategies between different organisms in an ecosystem. In SOS, the three common types of symbiotic relationships (mutualism, commensalism, and parasitism) are modeled using simple expressions, which are used to find the global minimum of the fitness function. Unlike other optimization methods, SOS has no parameters to be tuned, which makes it an attractive and easy-to-implement optimization method. Here, SOS is used to design a high speed symmetric switching CMOS inverter, which is considered the most fundamental logic gate. SOS results are compared to those obtained using several optimization methods, like particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), and other ones, available in the literature. It is shown that the SOS is a robust straight-forward evolutionary algorithm that can compete with other well-known advanced methods.

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Power Optimization of Three Dimensional Turbo Code Using a Novel Modified Symbiotic Organism Search (MSOS) Algorithm

Cited by 22 publications

References 29 publications

Doğru Akım Motor Sürücüleri için PI Parametrelerinin Simbiyotik Organizmalar Arama Algoritması ile Optimal Ayarı

Doğru Akım Motor Sürücüleri için PI Parametrelerinin Simbiyotik Organizmalar Arama Algoritması ile Optimal Ayarı

Optimal design of analog active filters using symbiotic organisms search

Optimal design of symmetric switching CMOS inverter using symbiotic organisms search algorithm

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