ANFIS Based Firing Angle Control of TSC-TCR for Reactive Power Compensation
Dixon J., Moran L., Rodriguez J. and Domke R., 2005. Reactive power compensation technologies: State-of-the-art review, Proc IEEE, 93: 2144-2164,
Gyugyi L., 1979. Reactive power generation and control by thyristor circuits, IEEE Trans. Ind. Appl., 5, 521-532,
Bayindir R., Sagiroglu S. and Colak I., 2009. An intelligent power factor corrector for power system using artificial neural networks, Electr. Power Syst. Res., 79:152-160,
Dalci K. B., Uzunoglu M. and Kucukdemiral I. B., 2004. Genetic algorithm based optimal self-tuning fuzzy logic controller for power system static VAR stabiliser," Int J Electr Eng Educ, 41:71-89,
Colak, I. Bayindir R. and Bay, Ö. F. 2003. Reactive power
compensation using a fuzzy logic controlled synchronous motor, Energy Conversion and Management, 44:2189-2204,
Kulkarni D. and Udupi G., 2009. Optimum switching of TSC-TCR using GA trained ANN for minimum harmonic injection, in 2009 2nd International Conference on Emerging Trends in Engineering and Technology (ICETET), , 527-532.
Sujanarko B., Ashari M. and M. H. Purnomo, 2010. Universal Algorithm Control for Asymmetric Cascaded Multilevel Inverter, International Journal of Computer Applications 8:0975–8887.
Mathur R. M. and Varma R. K., 2002. Thyristor-Based FACTS Controllers for Electrical Transmission Systems. John Wiley & Sons.
Jang J. R., 1993. ANFIS: adaptive-network-based fuzzy inference system, Systems, Man and Cybernetics, IEEE Transactions on, 23:665-685.
Al-Hmouz, A., Shen, J., Al-Hmouz R., and Yan J., 2012. Modeling and simulation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for mobile learning, Learning Technologies, IEEE Transactions on, 5:226-237.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.