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	Dynamic learning from neural control for strict-feedback systems with guaranteed predefined performance (EI收录)
	Wang, Min[1]; Wang, Cong[1]; Shi, Peng[2,3,4]; Liu, Xiaoping[5]
刊名	IEEE Transactions on Neural Networks and Learning Systems
	2015
卷号	PP页码:2564-2576
关键词	Backstepping Closed loop control systems Closed loop systems Feedback Feedback control Nonlinear feedback Radial basis function networks State feedback System theory
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2210839
专题	华南理工大学
作者单位	1.[1] Guangzhou Key Laboratory of Brain Computer Interaction and Applications, School of Automation Science and Engineering, South China University of Technology, Guangzhou 2.510641, China 3.[2] School of Electrical and Electronic Engineering, University of Adelaide, Adelaide 4.SA 5.5005, Australia 6.[3] College of Engineering and Science, Victoria University, Melbourne 7.VIC 8.8001, Australia 9.[4] College of Automation, Harbin Engineering University, Harbin 10.150001, China
推荐引用方式 GB/T 7714	Wang, Min[1],Wang, Cong[1],Shi, Peng[2,3,4],等. Dynamic learning from neural control for strict-feedback systems with guaranteed predefined performance (EI收录)[J]. IEEE Transactions on Neural Networks and Learning Systems,2015,PP:2564-2576.
APA	Wang, Min[1],Wang, Cong[1],Shi, Peng[2,3,4],&Liu, Xiaoping[5].(2015).Dynamic learning from neural control for strict-feedback systems with guaranteed predefined performance (EI收录).IEEE Transactions on Neural Networks and Learning Systems,PP,2564-2576.
MLA	Wang, Min[1],et al."Dynamic learning from neural control for strict-feedback systems with guaranteed predefined performance (EI收录)".IEEE Transactions on Neural Networks and Learning Systems PP(2015):2564-2576.

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