Fuzzy controller based output power leveling enhancement for a permanent magnet synchronous generator

Author(s):  
Abdul Motin Howlader ◽  
Naomitsu Urasaki ◽  
Shantanu Chakraborty ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
...  
2021 ◽  
Author(s):  
Satya Prasad Mohapatra ◽  
Aksaya Kumar Patra ◽  
Debswarup Rath ◽  
Sajeeb Kumar Kar ◽  
Dillip Kumar Subudhi ◽  
...  

Author(s):  
N. Selvaganesan

This chapter presents the design methodology of fuzzy based modeling, control, and fault diagnosis of Permanent Magnet Synchronous Generator (PMSG) system. The fuzzy based modeling scheme for PMSG is developed using the general Takagi-Sugeno fuzzy model. Subsequently, fuzzy controller is designed and simulated to maintain three phase output voltage as constant by controlling the speed of generator. The feasibility of the fuzzy model and control scheme is demonstrated using various operating conditions by MATLAB simulation. Also, fuzzy based fault detection scheme for PMSG is developed and presented. The positive and negative sequence currents are used as fault indicators and given as inputs to fuzzy fault detector. The fuzzy inference system is created, and rule base is evaluated, relating the sequence current component to the type of faults. The feasibility of this scheme is demonstrated for different types of fault under various operating conditions using MATLAB/Simulink.


Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2953 ◽  
Author(s):  
Chang ◽  
Tsai ◽  
Lu

The current control of the permanent-magnet synchronous generator (PMSG) using an interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy systems is designed and implemented. PMSG is an energy conversion unit widely used in wind energy generation systems and energy storage systems. Its performance is determined by the current control approach. IT2 T-S fuzzy systems are implemented to deal with the nonlinearity of a PMSG system in this paper. First, the IT2 T-S fuzzy model of a PMSG is obtained. Second, the IT2 T-S fuzzy controller is designed based on the concept of parallel distributed compensation (PDC). Next, the stability analysis can be conducted through the Lyapunov theorem. Accordingly, the stability conditions of the closed-loop system are expressed in Linear Matrix Inequality (LMI) form. The AC power from a PMSG is converted to DC power via a three-phase six-switch full bridge converter. The six-switch full bridge converter is controlled by the proposed IT2 T-S fuzzy controller. The analog-to-digital (ADC) conversion, rotor position calculation and duty ratio determination are digitally accomplished by the microcontroller. Finally, simulation and experimental results verify the performance of the proposed current control.


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