Online Adaptive Error Compensation SVM-Based Sliding Mode Control of an Unmanned Aerial VehicleReport as inadecuate




Online Adaptive Error Compensation SVM-Based Sliding Mode Control of an Unmanned Aerial Vehicle - Download this document for free, or read online. Document in PDF available to download.

International Journal of Aerospace Engineering - Volume 2016 2016, Article ID 8407491, 14 pages -

Research ArticleCollege of Automation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Received 14 October 2015; Accepted 27 January 2016

Academic Editor: Kenneth M. Sobel

Copyright © 2016 Kaijia Xue et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Unmanned Aerial Vehicle UAV is a nonlinear dynamic system with uncertainties and noises. Therefore, an appropriate control system has an obligation to ensure the stabilization and navigation of UAV. This paper mainly discusses the control problem of quad-rotor UAV system, which is influenced by unknown parameters and noises. Besides, a sliding mode control based on online adaptive error compensation support vector machine SVM is proposed for stabilizing quad-rotor UAV system. Sliding mode controller is established through analyzing quad-rotor dynamics model in which the unknown parameters are computed by offline SVM. During this process, the online adaptive error compensation SVM method is applied in this paper. As modeling errors and noises both exist in the process of flight, the offline SVM one-time mode cannot predict the uncertainties and noises accurately. The control law is adjusted in real-time by introducing new training sample data to online adaptive SVM in the control process, so that the stability and robustness of flight are ensured. It can be demonstrated through the simulation experiments that the UAV that joined online adaptive SVM can track the changing path faster according to its dynamic model. Consequently, the proposed method that is proved has the better control effect in the UAV system.





Author: Kaijia Xue, Congqing Wang, Zhiyu Li, and Hanxin Chen

Source: https://www.hindawi.com/



DOWNLOAD PDF




Related documents