Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

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Author: search.filters.author.Kamble, S.B.

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    System simulation approach for helicopter autopilot
    (Institute of Electrical and Electronics Engineers Inc., 2014) Jamadagni, C.S.; Chethan, C.U.; Jeppu, Y.V.; Kamble, S.B.; Desai, V.
    This paper discusses an approach for system simulation of an autopilot system designed for a Bell helicopter model. The flight controls for the helicopter is designed in Matlab/Simulink and the same is visualized in X-Plane flight simulator. The approach involves software in loop simulation method where controls are designed in Matlab/Simulink and the responses are observed on X-Plane plant. The interaction between the Matlab/Simulink and X-Plane is through UDP. A parameter identification of the X-Plane model is carried out from data obtained through UDP. This simulation setup is a good way to learn the intricacies of systems development, plant identification and control. © 2014 IEEE.
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    System identification for helicopter longitudinal dynamics model - Best practices
    (Institute of Electrical and Electronics Engineers Inc., 2015) Kamble, S.B.; Desai, V.; Jeppu, Y.V.; Prajna
    For estimation of mathematical model and parameters of a system, the system identification has been widely applied in various domains such as the automatic control, aviation, spaceflight, civil and mechanical engineering, medicine, biology, chemical processes, marine ecology, geology etc. The main aim of this work is to perform preliminary studies to design a control law for helicopter model making it as autopilot. X-plane flight simulator will be used with Matlab wherein the estimated model is imported and simulated for its practical behavior. A longitudinal state-space model of the Puma, SA330 research helicopter is used as a reference model. First, the model is described and with standard reference input test signals, output data set is generated, then this input-output dataset is used for system identification purpose. Both traditional methods such as subspace & prediction-error minimization (PEM) method along with modern ways of identification methods such as neural networks are used. A practical comparison between used identification methods and best suitable type of input for estimation is discussed. © 2015 IEEE.