FPGA implementation of NN based LMS–LMF control algorithm in DSTATCOM for power quality improvement

Abstract

Neural Network (NN) based Least Mean Square (LMS)–Least Mean Fourth (LMF) control technique is developed and implemented in Field Programmable Gate Array (FPGA) for Shunt Active Power Filter (SAPF) to enhance Power Quality (PQ) in three-phase four wire distribution system. The PQ enhancement comprises the improvement of power factor, mitigation of harmonics and compensation of reactive power. The proposed control strategy is simulated in MATLAB/Simulink to determine the reference source currents and weights of active and reactive components. The simulation results of LMS–LMF control are compared with the other three control strategies. The NN control is developed as individual modules in FPGA. Thus it can be configured to any other research area which has identical requirements. The FPGA implementation overcomes the drawback of conventional controllers with a fast and accurate response. The FPGA based proposed control strategy for SAPF is developed as a laboratory prototype and the results obtained are analyzed. The results attained adhere to power quality standards.