期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2016
卷号：11
期号：8
页码：53-64
出版社：SERSC
摘要：Intelligent robot not only can realize reservation on conduct and actions, but also can be understand the characteristics of the unknown environment and adapt to changes in the environment through their own "sensory system", robots get outside information mainly by vision, this paper take the joint robot of binocular robot vision system as control plant, pointing on the problem of the uncertainties that existed in the dynamic model of binocular vision robot may cause instability. This paper has proposed a sliding model control scheme with RBF neural network adaptive control strategy based on sub-block approximation algorithm, in this control method, sliding model control was used to control trajectory of the joints of robot, and utilize the RBF neural network to approximate the each uncertain in the dynamic model of robot. The simulation results show that compared with the RBF neural network adaptive control strategy based on integral approximation for uncertainness, the proposed control method has features with good position tracking.
关键词：Binocular vision robot; Sliding model control; Model approximation; ;RBF neural network; ;Sub-block approximation
