Optimizing Neuro-Fuzzy Fault Diagnostic Algorithm for Photovoltaic Systems
نویسندگان
چکیده
The main goal of this research is to develop a novel optimum neuro-fuzzy system for diagnosis the complex and dynamic systems. .It has used the Particle Swarm Optimization (PSO) technique for training the Adaptive Neuro Fuzzy Inference System (ANFIS) off-line. The proposed system has applied for diagnosis the faults of two complex Photovoltaic (PV) systems. They are used to feed the power for lighting and pumps in a synchrotron building inside a radiation centre and the power for a house in a rural village. Its achieved results are compared with three ANFIS' diagnostic systems. They are: traditional neuro-fuzzy diagnostic systems, optimized ANFIS with genetic algorithm, optimized ANFIS with gradient descendent technique. The suggested system has proved its good performance to be applied for diagnose the complex dynamic systems.
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