Artificial Neural Network Compensation Technique for A PD Controlled Inverted Pendulum

Hagar, Mohamed Osman Hamad; Supervisor,- AwadallaTayfor Ali

dc.contributor.author	Hagar, Mohamed Osman Hamad
dc.contributor.author	Supervisor,- AwadallaTayfor Ali
dc.date.accessioned	2014-05-05T10:00:09Z
dc.date.available	2014-05-05T10:00:09Z
dc.date.issued	2012-09-01
dc.identifier.citation	Hagar,Mohamed Osman Hamad .Artificial Neural Network Compensation Technique for A PD Controlled Inverted Pendulum/Mohamed Osman Hamad Hagar;AwadallahTayfor Ali.-Khartoum:Sudan University of Science and Technology,College of Engineering,2012.-44p. : ill. ; 28cm.-M.Sc.	en_US
dc.identifier.uri	http://repository.sustech.edu/handle/123456789/4780
dc.description	Thesis	en_US
dc.description.abstract	This study presents the design of the decoupled neural network reference compensation technique (DNNRCT). The technique is applied to the control of a two degrees-of-freedom inverted pendulum mounted on an x-y table. Neural networks are used as auxiliary controllers for both the X axis and Y axis of the PD controlled inverted pendulum. The DRCT method is used to compensate for uncertainties at the trajectory level and used to control both the angle of a pendulum and the position of a cart simultaneously.	en_US
dc.description.sponsorship	Sudan University of Science and Technology	en_US
dc.language.iso	en	en_US
dc.publisher	Sudan University of Science and Technology	en_US
dc.subject	Electrical Engineering	en_US
dc.subject	Microprocessor and Control	en_US
dc.subject	Artificial Neural Networks	en_US
dc.subject	A PD Controlled Inverted Pendulum	en_US
dc.title	Artificial Neural Network Compensation Technique for A PD Controlled Inverted Pendulum	en_US
dc.title.alternative	‫تقنية تعويض الشبكات العصبية الا‫‬صطناعية فى المتحكم التناسبي التفاضلى للبندول المعكوس‬	en_US
dc.type	Thesis	en_US