UKF-based Active Modeling and Model-reference Adaptive Control for Mobile Robots
SONG Qi1,2, HAN Jianda1
1. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; 2. Graduate School of the Chinese Academy of Sciences, Beijing 100039, China
宋崎, 韩建达. 基于UKF的移动机器人主动建模及模型自适应控制方法[J]. 机器人, 2005, 27(3): 226-230,235..
SONG Qi, HAN Jianda. UKF-based Active Modeling and Model-reference Adaptive Control for Mobile Robots. ROBOT, 2005, 27(3): 226-230,235..
Abstract：The Unscented Kalman Filter (UKF) is employed to build an online model for mobile robots by means of joint estimation of states and parameters. Based on this active model, the inverse dynamic control (IDC) is further proposed to make the robot autonomously adaptive to its internal uncertainties. Extensive simulations are conducted with respect to the dynamics of an omni-directional mobile robot. The convergence and tracking ability as well as the uncertainty bound of UKF to estimate time-varying states and parameters are presented. Results of the IDC enhanced by active estimation are also compared with those of a classic PD control with constant gains to demonstrate the effectiveness of the control scheme.
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