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1篇 您的检索式：作者名="Aurobinda Bag"

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		题名	作者	年代	出处	被引量
	1	A Combined Reinforcement Learning and Sliding Mode Control Scheme for Grid Integration of a PV System显示文摘The paper presents development of a reinforcement learning(RL)and sliding mode control(SMC)algorithm for a 3-phase PV system integrated to a grid.The PV system is integrated to grid through a voltage source inverter(VSI),in which PVVSI combination supplies active power and compensates reactive power of the local non-linear load connected to the point of common coupling(PCC).For extraction of maximum power from the PV panel,we develop a RL based maximum power point tracking(MPPT)algorithm.The instantaneous power theory(IPT)is adopted for generation reference inverter current(RIC).An SMC algorithm has been developed for injecting current to the local non-linear load at a reference value.The RL-SMC scheme is implemented in both simulation using MATLAB/SIMULINK software and on a prototype PV experimental.The performance of the proposed RL-SMC scheme is compared with that of fuzzy logic-sliding mode control(FL-SMC)and incremental conductance-sliding mode control(IC-SMC)algorithms.From the obtained results,it is observed that the proposed RL-SMC scheme provides better maximum power extraction and active power control than the FL-SMC and IC-SMC schemes.	Aurobinda Bag Bidyadhar Subudhi Pravat Kumar Ray	2019	CSEE Journal of Power and Energy Systems2019，5，4：	3

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