Hybrid Cfd-Nnarx Modelling Of Single Mrf Valve For Visual Servoing.

Magnetorheological fluid (MRF) actuator emerged in the last decade as a potential system to replace electro-hydraulic servo system in precision applications. A complete closed-loop control system is necessary to support the accuracy of the system. Modelling of the valve is a crucial task in devel...

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書誌詳細
第一著者: Abu Bakar, Muhamad Husaini
フォーマット: 学位論文
言語:English
出版事項: 2017
主題:
オンライン・アクセス:http://eprints.usm.my/36462/1/MUHAMAD_HUSAINI_ABU_BAKAR_24_Pages.pdf
http://eprints.usm.my/36462/
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要約:Magnetorheological fluid (MRF) actuator emerged in the last decade as a potential system to replace electro-hydraulic servo system in precision applications. A complete closed-loop control system is necessary to support the accuracy of the system. Modelling of the valve is a crucial task in developing an optimal control system for the valve, but the knowledge of fluid behaviour inside the valve channel remains scarce. This research aims to develop a plant model of MRF actuator using the system identification approach, where the Computational Fluid Dynamics (CFD) result is used as an input. The plant model is then used to design a closed-loop control system for the MRF actuator. To achieve this objective, a 3D CFD model was developed, and a steady state analysis was run to study fluid behaviours in the channel. Transient analysis with dynamic input was further performed to study the correlation between the current input and the volume flow rate as an output. Neural network nonlinear autoregressive network with exogenous inputs (NNARX) used data from the CFD to identify the plant model of an MRF valve. The result acquired from the CFD simulation and plant model gave good agreement with the experimental result with an error of less than 3%. The velocity in the MRF valve reduced 85% when the current varied from 0 to 0.8A. The hybrid CFD-NNARX model shows a small deviation from the experimental result with an average error of 4%. As a conclusion, the hybrid CFDNNARX has been proven useful in modelling the MRF actuator. The main contribution of this work is the plant model of an MRF actuator, which can be utilised as an input in controller design process of MRF actuator.