Author: Jiang, Bailun
Title: High precision tracking of UAV
Advisors: Wen, Chih-yung (ME)
Lu, Peng (ME)
Degree: M.Sc.
Year: 2021
Subject: Drone aircraft
Drone aircraft -- Control systems
Hong Kong Polytechnic University -- Dissertations
Department: Department of Mechanical Engineering
Pages: xii, 74 pages : color illustrations
Language: English
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.
Rights: All rights reserved
Access: restricted access

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