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dc.contributorDepartment of Mechanical Engineeringen_US
dc.contributor.advisorWen, Chih-yung (ME)en_US
dc.contributor.advisorLu, Peng (ME)en_US
dc.creatorJiang, Bailun-
dc.publisherHong Kong Polytechnic Universityen_US
dc.rightsAll rights reserveden_US
dc.titleHigh precision tracking of UAVen_US
dcterms.abstractIn 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.extentxii, 74 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.educationalLevelAll Masteren_US
dcterms.LCSHDrone aircraften_US
dcterms.LCSHDrone aircraft -- Control systemsen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.accessRightsrestricted accessen_US

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