Comparative study of sliding mode and ANFIS based observers for speed & position sensor-less control of variable speed PMSG

This paper presents a novel speed & position estimation algorithm for the PMSG based wind turbine using Adaptive Network-Based Fuzzy Inference System (ANFIS). The precise information of rotor speed and position is required to perform maximum power tracking in variable speed wind turbine, which is very difficult to estimate under varying operating conditions, as it may lead to parameter variation such as stator resistance, inductance and torque constant. To neutralize the effect of parameter variation, an ANFIS based adaptive model is developed to track the rotor position and speed accurately in the whole range of low to high speed under varying wind conditions. A detailed comparison of two different estimation techniques based on adaptive neuro-fuzzy system and sliding mode observers is also provided under varying speed with variable PMSG parameters. Both of the estimation techniques are realized and simulated in MATLAB/SPS environment. The simulation results under dynamic operating conditions are provided to demonstrate the effectiveness of proposed approach.