DocumentCode :
2287566
Title :
Adaptive visual servo control of UAV Ground-Target-Autonomous-Tracking System
Author :
Chen, Longsheng ; Jiang, Yang ; Wang, Changkun
Author_Institution :
Sch. of Aircraft Eng., Nanchang HangKong Univ., Nanchang, China
fYear :
2012
fDate :
6-8 July 2012
Firstpage :
133
Lastpage :
137
Abstract :
A novel adaptive servo control method is proposed for UAV GTATS(Ground-Target-Autonomous-Tracking System),which consists of basic control law for UAV and visual tracking controller for GTATS. The adaptive servo control method only depends on target information in the image plane and Kalman filtering technology. Based on this proposed method, a dynamic motion target can be tracked without target´s 3D velocity. Synchronously, in order to estimate the optimal system state and target image velocity which is used later by the visual tracking controller, a self-tuning Kalman filter is adopted to estimate interesting parameters on-line in real-time. Further, Because the visual tracking controller is working entirely in image space, the dynamic characteristics of the image signal are analyzed and a kinematics model is developed for the target in the image plane by the geometrical relations among the UAV, the target and the camera. Finally, The performance of the controller is demonstrated by theoretical stability analysis.
Keywords :
Kalman filters; adaptive control; autonomous aerial vehicles; geometry; parameter estimation; self-adjusting systems; stability; state estimation; target tracking; vehicle dynamics; velocity control; visual servoing; 3D velocity; Kalman filtering technology; UAV GTATS; UAV ground-target-autonomous-tracking system; adaptive visual servo control; control law; dynamic characteristics; dynamic motion target tracking; geometrical relations; image plane; image signal; image space; kinematics model; optimal system state estimation; parameter estimation; self-tuning Kalman filter; stability analysis; target image velocity; visual tracking controller; Decision support systems; Field-flow fractionation; Iron; Dynamic target tracking; Self-tuning Kalman filter; Visual servo control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
Type :
conf
DOI :
10.1109/WCICA.2012.6357854
Filename :
6357854
Link To Document :
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