CHITRA V
@psgitech.ac.in
Associate Professor
PSG institute of technology and applied research
RESEARCH INTERESTS
Graph decomposition, Graph factorizations, graph labellings
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
Karthikeyan Ramasamy, Arivoli Sundaramurthy, and Chitra Vaithiyalingam
IOS Press
The primary goal is to enhance the PSN by maintaining stable and consistent MGS operation and reestablishing stable operating conditions after generational interruptions. The artificial neural network is created using a bio-inspired optimization algorithm, such as particle swarm optimization, second generation particle swarm optimization, and new model particle swarm optimization., which directs the evolutionary learning process to determine the most optimal solution. For the best result, the ANN and bio-inspired algorithm (BIANN) are coupled. The suggested BIANN-based controller is made comprised of an internal current and an external power loop. The proper PI gain parameter is tuned using BIANN, allowing the MGS to be stable. Three PSOs are used to investigate the suggested method, and the Matlab Simulink platform is used to create the fitness functions. The results are examined and contrasted. The new model’s particle swarm optimization provides MGS functioning and stability that is largely accurate and reliable.
P. Reba, S. Mohandass, V. Chitra, and M. M. Suriyaa
Springer Science and Business Media LLC
S. Arivoli, R. Karthikeyan, and V. Chitra
IEEE
V. Chitra, A. Shanmuga Vadivu, and A. Muthusamy
Springer Science and Business Media LLC
V. Chitra and Appu Muthusamy
Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Gora
V. Chitra and A. Muthusamy
Elsevier BV