Adaptive sliding mode control using RBF Neural Network for nonlinear system

	Adaptive sliding mode control using RBF Neural Network for nonlinear system
	Zhang, Ming-Guang; Chen, Yu-Wu; Wang, Peng; Wang, Zhao-Gang
	2008
关键词	adaptive sliding mode control RBF neural network feed back linearization inverted pendulum
页码	1860-1865
英文摘要	A novel adaptive sliding mode controller based oil Radial Basis Function neural network (RBFNN) Is proposed in this paper for life nonlinear systems with uncertainties using feetback linearization method. An adaptive rule Is utilized to on-line adjusting the weights of RBFNN, which Is used to compute the equivalent control. Adaptive training algorithm was derived if the sense of Lyapunov stability analysis. so that the stability of the dosed-loop system can be guaranteed even In the case of uncertainty. Using the RBFNN. Instead of multilayer feed forward network trained with back propagation, works out shorter reaching time. Chattering problem of SMC is substantially derived lit file proposed controller. Simulation results show that file position trucking responses closely follow the desired trajectory occurrence of the disturbances. Also, simulation results demonstrate that. the proposed controller is a stable control scheme for the inverted pendulum trajectory tracking applications and has strong robustness.
会议录	PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
WOS研究方向	Computer Science ; Engineering ; Robotics
WOS记录号	WOS:000259604901010
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/37974]
专题	电气工程与信息工程学院
通讯作者	Zhang, Ming-Guang
作者单位	Lanzhou Univ Technol, Sch Elect & Informat Engn, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Ming-Guang,Chen, Yu-Wu,Wang, Peng,et al. Adaptive sliding mode control using RBF Neural Network for nonlinear system[C]. 见:.