Hybrid Neuro-Fuzzy controller based Adaptive Neuro-Fuzzy Inference System Approach for Multi-Area Load Frequency Control of Interconnected Power System
|International Journal of Electrical and Electronics Engineering|
|© 2016 by SSRG - IJEEE Journal|
|Volume 3 Issue 1|
|Year of Publication : 2016|
|Authors : O Anil Kumar, Ch Rami Reddy|
O Anil Kumar, Ch Rami Reddy, "Hybrid Neuro-Fuzzy controller based Adaptive Neuro-Fuzzy Inference System Approach for Multi-Area Load Frequency Control of Interconnected Power System" SSRG International Journal of Electrical and Electronics Engineering 3.1 (2016): 17-25.
O Anil Kumar, Ch Rami Reddy,(2016). Hybrid Neuro-Fuzzy controller based Adaptive Neuro-Fuzzy Inference System Approach for Multi-Area Load Frequency Control of Interconnected Power System. SSRG International Journal of Electrical and Electronics Engineering 3(1), 17-25.
The paper concentrated on an advanced control strategy is proposed in the multi area networks. In this a novel load frequency control technique which is implemented under the power system has unknown variable functions. The system is controlled with the help of adaptive neuro fuzzy interface system arrangement with the integration of LFC at abnormal conditions as unknown parameter considerations. Here a supplementary control algorithm is implemented to eliminate for the errors in the multi area system also to eliminate fuzzy errors and to get good performance H∞ tracking arrangement. Here the neuron functions and LFC techniques are provided for to create the closes loop arrangement with tracking. An advanced control algorithm which is designed to compensate the disturbances by improving the steady stare responses and transient response in the multi area networks. The designed simulink models are testes and verified within MATLAB/SIMULINK with reduced fluctuations in the networks.
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Adaptive control, adaptive fuzzy control, fuzzy approximation, GDB, GRC, load frequency control (LFC), multi-area, Anfis controller.