Karthikeyan S
@jjcet.ac.in
Assistant Professor, Department of Electrical and Electronics Engineering
JJ college of Engineering and Technology
EDUCATION
B.Tech (EEE)
ME (Power Electronics and Drives)
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Artificial Intelligence, Industrial and Manufacturing Engineering
Scopus Publications
Scopus Publications
Sureshraj Se Pa, Mohamed Badcha Yakoob, Priya Maruthai, Karthikeyan Singaravelu, Nalini Duraisamy, Rathi Devi Palaniappan, and John Britto Pithai
MDPI
: The combined action of Machine Learning and the control system algorithm is proposed in this Renewable Energy System. The reason for proposing this Renewable Energy System is because it is a clean energy source from nature and it is free of cost. Here, the Renewable Energy system includes the Solar PV. This energy system has a higher scope of installation in most countries. For that, we propose a controller which achieves high performance and Guarantees Stability. In this proposed system, the disturbance and Uncertain parameters are considered both internal and external parameters. To overcome this problem, the Robust Control design is already implemented in the Control Engineering Field to attain System Stability. Conversely, this proposed method is a new approach to examine the System Stability by combining Machine Learning Gaussian Process Regression (MLGPR) with the Robust H-infinity Controller. The approach used in Machine Learning-GPR consists of gathering data of the initial system and gradually decreasing the Uncertainty, which results in an improvement of the performance. Finally, ML-GPR learns a model with Uncertainty bounds. We combined the model with a Control Framework (i.e., H-infinity Controller) that Guarantees Stability for this uncertain model. The design Environment used for the experimental verification is MATLAB/Simulink software. The Simulation Results confirmed the effectiveness of the newly proposed Control Strategy.