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Browsing by Author "Kamal, Tariq"

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A novel switched model predictive control of wind turbines using artificial neural network-Markov chains prediction with load mitigation

Pervez, Mahum; Kamal, Tariq; Fernandez-Ramirez, Luis M. M. (ELSEVIER, 2022)

The existing model predictive control algorithm based on continuous control using quadratic programming is currently one of the most used modern control strategies applied to wind turbines. However, heavy computational ...
Dağıtılmış enerji kaynaklarının ve mikro şebekelerin uyarlamalı ve hesaplamalı zekâ denetimi = Adaptive and computational intelligence control of distributed energy sources and microgrids

Kamal, Tariq (Sakarya Üniversitesi, 2022)

Modern elektrik güç dağıtım sistemleri, evsel ve endüstriyel yüklerin artan elektrifikasyonu ve yenilenebilir enerji kaynaklarının (rüzgâr, fotovoltaik güneş, yakıt hücresi, hidro elektrik santraller) ve ulaşımın (elektrikli ...
Fast Adaptive Robust Differentiator Based Robust-Adaptive Control of Grid-Tied Inverters with a New L Filter Design Method

Kamal, Tariq; Karabacak, Murat; Kilic, Fuat; Blaabjerg, Frede; Fernandez-Ramirez, Luis M. (MDPI, 2020)

In this research, a new nonlinear and adaptive state feedback controller with a fast-adaptive robust differentiator is presented for grid-tied inverters. All parameters and external disturbances are taken as uncertain in ...
Hybrid fuzzy-genetic algorithm to automated discovery of prediction rules

Fadel, Ibrahim A.; Alsanabani, Hussein; Oz, Cemil; Kamal, Tariq; Iskefiyeli, Murat; Abdien, Fawzia (IOS PRESS, 2021)

Genetic algorithm is one of data mining classification techniques and it has been applied successfully in a wide range of applications. However, the performance of Genetic algorithm fluctuates significantly. This research ...
Novel Improved Adaptive Neuro-Fuzzy Control of Inverter and Supervisory Energy Management System of a Microgrid

Kamal, Tariq; Karabacak, Murat; Peric, Vedran S.; Hassan, Syed Zulqadar; Fernandez-Ramirez, Luis M. (MDPI, 2020)

In this paper, energy management and control of a microgrid is developed through supervisor and adaptive neuro-fuzzy wavelet-based control controllers considering real weather patterns and load variations. The supervisory ...