@Article{cmes.2020.08908,
AUTHOR = {M. Sujith, S. Padma},
TITLE = {Implementation of PSOANN Optimized PI Control Algorithm for Shunt Active Filter},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {122},
YEAR = {2020},
NUMBER = {3},
PAGES = {863--888},
URL = {http://www.techscience.com/CMES/v122n3/38378},
ISSN = {1526-1506},
ABSTRACT = {This paper proposes the optimum controller for shunt active filter (SAF) to 
mitigate the harmonics and maintain the power quality in the distribution system. It consists 
of shunt active filter, Voltage Source Inverter (VSI), series inductor and DC bus and nonlinear load. The proposed hybrid approach is a combination of Particle Swarm 
Optimization (PSO) and Artificial Neural Network (ANN) termed as PSOANN. The PI 
controller gain parameters of k<sub>p</sub> and k<sub>i</sub> are optimized with the help of PSOANN. The 
PSOANN improves the accuracy of tuning the gain parameters under steady and dynamic 
load conditions; thereby it reduces the values of THD within the prescribed limits of IEEE 
519. The PSO optimizes the dataset of terminal voltage and DC voltage present in shunt 
active filter for different load condition. The optimized dataset acts as the input for the 
controller to predict the optimal gain with minimal error and to generate the optimized 
control signal for the SAF. The proposed methodology is modelled and simulated with the 
help of MATLAB/Simulink platform and illustrated the few test cases considered for 
exhibiting the performance of proposed hybrid controller. The experimental results are 
measured with developed laboratory prototype and compared with the simulation results to 
validate the effectiveness of the proposed control methodology.},
DOI = {10.32604/cmes.2020.08908}
}