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Wyświetlanie 1-2 z 2
Tytuł:
An Analytical Study for the Role of Fuzzy Logic in Improving Metaheuristic Optimization Algorithms
Autorzy:
Vij, Sonakshi
Jain, Amita
Tayal, Devendra
Castillo, Oscar
Powiązania:
https://bibliotekanauki.pl/articles/385121.pdf
Data publikacji:
2018
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
fuzzy logic
metaheuristics
evolutionary computing
genetic algorithm
particle swarm optimization (PSO)
ant colony optimization
fuzzy evolutionary algorithm
fuzzy cuckoo
fuzzy simulated annealing
fuzzy swarm intelligence
fuzzy differential evolution
tabu
fuzzy mutation
fuzzy natural selection
fuzzy fitness function
big bang big crunch
fuzzy bacterial
neuro fuzzy logic
logika rozmyta
metaheurystyka
obliczenia ewolucyjne
algorytm genetyczny
optymalizacja roju cząstek
optymalizacja kolonii mrówek
Opis:
The research applications of fuzzy logic have always been multidisciplinary in nature due to its ability in handling vagueness and imprecision. This paper presents an analytical study in the role of fuzzy logic in the area of metaheuristics using Web of Science (WoS) as the data source. In this case, 178 research papers are extracted from it in the time span of 1989-2016. This paper analyzes various aspects of a research publication in a scientometric manner. The top cited research papers, country wise contribution, topmost organizations, top research areas, top source titles, control terms and WoS categories are analyzed. Also, the top 3 fuzzy evolutionary algorithms are extracted and their top research papers are mentioned along with their topmost research domain. Since neuro fuzzy logic poses feasible options for solving numerous research problems, hence a section is also included by the authors to present an analytical study regarding research in it. Overall, this study helps in evaluating the recent research patterns in the field of fuzzy metaheuristics along with envisioning the future trends for the same. While on one hand this helps in providing a new path to the researchers who are beginners in this field as they can start exploring it through the analysis mentioned here, on the other hand it provides an insight to professional researchers too who can dig a little deeper in this field using knowledge from this study.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2018, 12, 4; 11-27
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Study of Optimised Artificial Intelligence Based First Order Sliding Mode Controllers for Position Control of a DC Motor Actuator
Autorzy:
Nyong-Bassey, B. E.
Akinloye, B.
Powiązania:
https://bibliotekanauki.pl/articles/385114.pdf
Data publikacji:
2016
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
adaptive fuzzy control
DC motor position control
genetic algorithm
particle swarm optimization (PSO)
sliding mode control
Opis:
This paper aims at critically reviewing various sliding mode control measures applied to Permanent Magnet DC Motor actuator for position control. At first, a hybrid sliding mode controller was examined with its advantages and disadvantages. Then, the smooth sliding mode controller in the same manner. The shortcomings of the two methods were overcome by proper switch design and also using tanh-sinh hyperbolic function. The sliding mode controller switches on when either disturbance or noise is detected. Genetic Algorithm Computational tuning technique is employed to optimize the gains of the controllers for optimal response.The performance of the proposed controller architecture, as well as the reviewed controllers, have been compared for performance evaluation with respect to several operating conditions. This includes load torque disturbance injection, noise injection in a feedback loop, motor nonlinearity exhibited by parameters variation, and a step change in reference input demand.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2016, 10, 3; 58-71
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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