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DC Field | Value | Language |
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dc.contributor.author | Karna, Pankaj | |
dc.date.accessioned | 2023-04-20T10:57:00Z | - |
dc.date.available | 2023-04-20T10:57:00Z | - |
dc.date.issued | 2017-05 | |
dc.identifier.uri | http://10.1.7.192:80/jspui/handle/123456789/11480 | - |
dc.description.abstract | This 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.publisher | Institute of Technology | en_US |
dc.relation.ispartofseries | 15MICC07; | |
dc.subject | IC 2017 | en_US |
dc.subject | Project Report 2017 | en_US |
dc.subject | IC Project Report | en_US |
dc.subject | Project Report | en_US |
dc.subject | 15MIC | en_US |
dc.subject | 15MICC | en_US |
dc.subject | 15MICC07 | en_US |
dc.subject | Control & Automation | en_US |
dc.subject | Control & Automation 2017 | en_US |
dc.subject | IC (Control & Automation) | en_US |
dc.title | Modelling and Simulation of Advanced Control system | en_US |
dc.type | Dissertation | en_US |
Appears in Collections: | Dissertations, E&I |
Files in This Item:
File | Description | Size | Format | |
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15MICC07.pdf | 15MICC07 | 1.35 MB | Adobe PDF | ![]() View/Open |
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