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Title of Journal: Neural Comput Applic

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Abbravation: Neural Computing and Applications

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Springer London

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ISSN

1433-3058

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Solving timevarying quadratic programs based on f

Authors: Peng Miao Yanjun Shen Yuehua Huang YanWu Wang
Publish Date: 2014/10/18
Volume: 26, Issue: 3, Pages: 693-703
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Abstract

In this paper finitetime Zhang neural networks ZNNs are designed to solve timevarying quadratic program QP problems and applied to robot tracking Firstly finitetime criteria and upper bounds of the convergent time are reviewed Secondly finitetime ZNNs with two tunable activation functions are proposed and applied to solve the timevarying QP problems Finitetime convergent theorems of the proposed neural networks are presented and proved The upper bounds of the convergent time are estimated less conservatively The proposed neural networks also have superior robustness performance against perturbation with large implementation errors Thirdly feasibility and superiority of our method are shown by numerical simulations At last the proposed neural networks are applied to robot tracking Simulation results also show the effectiveness of the proposed methodsThis work was supported by the National Science Foundation of China Nos 61374028 61374171 51177088 61273183 61304162 the Grant National Science Foundation of Hubei Provincial 2013CFA050 and the Graduate Scientific Research Foundation of China Three Gorges University 2014PY064 2014PY069

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