Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/11480
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dc.contributor.authorKarna, Pankaj
dc.date.accessioned2023-04-20T10:57:00Z-
dc.date.available2023-04-20T10:57:00Z-
dc.date.issued2017-05
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/11480-
dc.description.abstractThis work elucidates a comparative study of highly non-linear and intricate Inverted Pendulum system using different soft computing methods. Primarily, a Fuzzy Logic controller was designed from Proportional-Derivative(PD) control. Balancing is a common control task. In this experiment, we will find control strategies that balance the pendulum in the upright position while maintaining a desired position of the arm. Furthermore, a Neural Networks(NN) controller was used to enhance the results obtained from Fuzzy Logic controller. Also, an Adaptive Neuro Fuzzy Inference System(ANFIS) controller was proposed and evaluated in context to both controllers. The proposed controllers are developed in MATLAB-Simulink. Finally, the study exemplifies the impact of variation(disturbance) on performance parameters of Inverted Pendulum system. The outcomes show that ANFIS controller offers better control compared to rest controllers. Included in this report.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries15MICC07;
dc.subjectIC 2017en_US
dc.subjectProject Report 2017en_US
dc.subjectIC Project Reporten_US
dc.subjectProject Reporten_US
dc.subject15MICen_US
dc.subject15MICCen_US
dc.subject15MICC07en_US
dc.subjectControl & Automationen_US
dc.subjectControl & Automation 2017en_US
dc.subjectIC (Control & Automation)en_US
dc.titleModelling and Simulation of Advanced Control systemen_US
dc.typeDissertationen_US
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