MODEL REFERENCE ADAPTIVE CONTROL USING NEURAL NETWORKS

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DC Field	Value	Language
dc.contributor.author	Shukla, Rohit	-
dc.date.accessioned	2019-05-16T11:55:02Z	-
dc.date.available	2019-05-16T11:55:02Z	-
dc.date.issued	2016-07	-
dc.identifier.uri	http://hdl.handle.net/123456789/14198	-
dc.description.abstract	The thesis presents a quick overview of Model Reference Adaptive Control (MRAC). The thesis presents model reference based neural network structure that can be used for adaptive control of linear and nonlinear processes. The proposed MRAC neural network scheme is simulated to control the movement of a simple, single-link robot arm. The simulation results show that neural network based MRAC can give satisfactory performance requirements	en_US
dc.description.sponsorship	ELECTRICAL ENGINEERING IITR	en_US
dc.language.iso	en	en_US
dc.publisher	ELECTRICAL ENGINEERING IITR	en_US
dc.subject	quick overview	en_US
dc.subject	Model Reference	en_US
dc.subject	Adaptive	en_US
dc.subject	network	en_US
dc.title	MODEL REFERENCE ADAPTIVE CONTROL USING NEURAL NETWORKS	en_US
dc.type	Other	en_US
Appears in Collections:	MASTERS' THESES (Electrical Engg)

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