Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Mechanical Engineering | en_US |
dc.contributor.advisor | Wen, Chih-yung (ME) | en_US |
dc.contributor.advisor | Lu, Peng (ME) | en_US |
dc.creator | Jiang, Bailun | - |
dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/11447 | - |
dc.language | English | en_US |
dc.publisher | Hong Kong Polytechnic University | en_US |
dc.rights | All rights reserved | en_US |
dc.title | High precision tracking of UAV | en_US |
dcterms.abstract | In this dissertation, a Neural Network-based Model Predictive Control (NNMPC) method is proposed to control a quadrotor for trajectory tracking task. First, a detailed dynamic model including hub forces, rolling moment, and motor dynamics is derived. To verify the model, a PID controller and a simulation programme was designed by Simulink. A cascaded Model Predictive Control (MPC) controller is developed then. The controller is developed by simplified mathematical quadrotor model with position reference in three axes. In order to achieve neural network based control, modelling of quadrotor system for multi-step prediction with neural network is studied. A novel neural network modelling structure is proposed. Feed-Forward Neural Network (FFNN) and Nonlinear Auto-Regressive eXogenous (NARX) are adopted for prediction. Then, NNMPC are developed by using neural network prediction model in MPC. Simulation results show that NNMPC with neural network prediction model trained by flight data has good trajectory tracking performance. | en_US |
dcterms.extent | xii, 74 pages : color illustrations | en_US |
dcterms.isPartOf | PolyU Electronic Theses | en_US |
dcterms.issued | 2021 | en_US |
dcterms.educationalLevel | M.Sc. | en_US |
dcterms.educationalLevel | All Master | en_US |
dcterms.LCSH | Drone aircraft | en_US |
dcterms.LCSH | Drone aircraft -- Control systems | en_US |
dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
dcterms.accessRights | restricted access | en_US |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
5924.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 4.23 MB | Adobe PDF | View/Open |
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