Madan Gopal

TL;DR: This paper presents an intelligent wind speed sensor less maximum power point tracking method for a variable speed wind energy conversion system (VS-WECS) based on a Q-Learning algorithm which is equipped with peak detection technique, which drives the system towards peak power even if learning is incomplete which makes the real time tracking faster.

TL;DR: In this paper, a model-free predictive control (MFPC) framework is proposed to take care of both the issues of conventional MPC and the excessive computational burden associated with the control optimization.

TL;DR: A dynamic evolving fuzzy neural network (DENFIS) function approximation approach to RL systems and results have demonstrated that the proposed approach performs well in reinforcement learning problems.

TL;DR: A reinforcement learning system based on the kernel recursive least-squares algorithm for continuous state-space is proposed and a KRLS-SVM algorithm for reinforcement learning is developed and demonstrated through case study - two-link robot manipulator.

TL;DR: The study of different topologies of Fuzzy logic based controller for the speed control of induction motors is presented.