By Xusheng Lei, Jianbo Su (auth.), Fu-Liang Yin, Jun Wang, Chengan Guo (eds.)
This ebook constitutes the court cases of the overseas Symposium on Neural N- works (ISNN 2004) held in Dalian, Liaoning, China duringAugust 19–21, 2004. ISNN 2004 obtained over 800 submissions from authors in ?ve continents (Asia, Europe, North the US, South the United States, and Oceania), and 23 nations and areas (mainland China, Hong Kong, Taiwan, South Korea, Japan, Singapore, India, Iran, Israel, Turkey, Hungary, Poland, Germany, France, Belgium, Spain, united kingdom, united states, Canada, Mexico, - nezuela, Chile, andAustralia). in response to experiences, this system Committee chosen 329 high quality papers for presentation at ISNN 2004 and ebook within the lawsuits. The papers are equipped into many topical sections less than eleven significant different types (theo- tical research; studying and optimization; aid vector machines; blind resource sepa- tion,independentcomponentanalysis,andprincipalcomponentanalysis;clusteringand classi?cation; robotics and keep watch over; telecommunications; sign, photograph and time sequence processing; detection, diagnostics, and computing device defense; biomedical functions; and different functions) protecting the complete spectrum of the hot neural community study and improvement. as well as the varied contributed papers, ?ve exceptional students have been invited to offer plenary speeches at ISNN 2004. ISNN 2004 was once an inaugural occasion. It introduced jointly a couple of hundred researchers, educators,scientists,andpractitionerstothebeautifulcoastalcityDalianinnortheastern China. It supplied a world discussion board for the individuals to provide new effects, to debate the cutting-edge, and to replace details on rising parts and destiny developments of neural community learn. It additionally created a pleasant chance for the contributors to fulfill colleagues and make buddies who proportion comparable learn interests.
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Additional info for Advances in Neural Networks - ISNN 2004: International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part II
Internal Force based Impedance Control for Cooperating Manipulators, in Proceedings of the IEEE International Conference on Robotics and Automation, vol. 3 (1993) 944-949 8. : Robot Force Control, Kluwer Academic, Boston (1999) 9. : ANFIS Synthesis by Hyperplane Clustering, in Proceedings of IFSA World Congress and 20th NAFIPS International Conference, vol 1 (2001) 340 -345 10. com Abstract. This paper presents an observer for robotic systems using FNN method to estimate the joint velocities of a robot, and then H∞ approach is embedded to attenuate the effect of external distributes and parametric uncertainties of the robotic systems.
1 flexible dual-arm space robot Fig. 1. 1, the front links 3, 5 are flexible. Define the robot’s generalized coordinate as p = ( x r1 , y r1 , θ1 , θ 2 , θ 3 , θ 4 , θ 5 , Q3T , Q5T ) T and task space coordinates as x a = ( x r1 , y r1 , θ1 , x e 3 , y e 3 , x e 5 , y e5 ) T , where ( x1r , y1r , θ1 ) T is the position and attitude vector of the vehicle. The contact force is defined as ~ f = ( f ex 3 , f ey 3 , f ex 5 , f ey 5 ) T , and the tip position vector is pe = ( xe 3 , y e3 , xe 5 , y e 5 ) T .
Thus we obtain the mapping model: f¨(k) = g f (k), f˙(k), p¨(k) , (2) where g (·) is a proper function. Since we have the same numbers of object features and control DOFs of the robot hand, Eq. (2) has the same dimensions of input and output. All coeﬃcient matrices generally have full ranks. , p¨(k) = g f (k), f˙(k), f¨(k) , (3) where g(·) is a properly deﬁned function. This model, called the visual mapping model, nonlinearly relates the hand movement to the motion of the object in image feature space.