Synchronous motor speed control based on ANFIS methodology and sliding mode observer

The use of renewable energies has increased in these last decades. The wind energy attracts more attention of several research studies. The control of the power generated by the wind turbine is very complicated. It requires the application of new techniques of control. This paper presents an application of Model reference adaptive system (MRAS) in the control of wind turbine power. The structure of the proposed MRAS consists of Neuro fuzzy (NF) controller and an adaptive system based on sliding mode controller (SMC). The use of NF and SMC methodologies is very interest and it allows improving the performances of the system control. The NF has the advantages of expert knowledge of the fuzzy inference system and the learning capabilities of neural networks. The use of SMC gives more flexibility to the adaptive system. According to digital simulation results, the designed MRAS-NF-SMC controller provides a good dynamic behaviour, and an excellent tracking of the requested trajectory

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Synchronous motor speed control based on ANFIS methodology and sliding mode observer

Cited by 3 publications

References 17 publications

Failure of Switch Five Levels Inverter Fault on Speed Sliding Mode Controller and Speed Sliding Adaptive Neuro Fuzzy Inference Controller of Induction Machine

Failure of Switch Five Levels Inverter Fault on Speed Sliding Mode Controller and Speed Sliding Adaptive Neuro Fuzzy Inference Controller of Induction Machine

Adaptive Neuro-Fuzzy Inference System Based Field Oriented Control of PMSM & Speed Estimation

Wind Turbine Control based on MRAS Methodology

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