A Linear Quadratic Regulation Controller Based on Radial Basis Function Network Approximation

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	A Linear Quadratic Regulation Controller Based on Radial Basis Function Network Approximation
	Liu C(刘超); Xu T(徐腾); Wei W(魏炜); Sun HM(孙何敏); Hou YH(侯永辉)
	2024-10-31
发表期刊	Electronics
卷号	13 期号:21 页码:4279-4294
摘要	This paper proposes a linear quadratic regulation(LQR)tracking control method based on a radial basis function(RBF)that successfully compensates for the shortcomings of the LQR method. The LQR method depends on the linearity of a model.Specifically,an RBF neural network is used to approximate and compensate for the nonlinear part of a controlled object in the PID type-I,type-II and type-III control loops to improve the performance of the system. Through the simulation of different industrial systems,such as underdamped,overdamped and critically damped systems,the method significantly improves the dynamic response performance indices,such as the rise time and settling time,of the system.
关键词	linear quadratic regulation radial basis function dynamic response performance
学科领域	天文技术与方法
语种	英语
文献类型	期刊论文
条目标识符	http://ir.niaot.ac.cn/handle/114a32/2245
专题	中国科学院南京天文光学技术研究所知识成果期刊论文
作者单位	南京天文光学技术研究所
推荐引用方式 GB/T 7714	Liu C,Xu T,Wei W,et al. A Linear Quadratic Regulation Controller Based on Radial Basis Function Network Approximation[J]. Electronics,2024,13(21):4279-4294.
APA	Liu C,Xu T,Wei W,Sun HM,&Hou YH.(2024).A Linear Quadratic Regulation Controller Based on Radial Basis Function Network Approximation.Electronics,13(21),4279-4294.
MLA	Liu C,et al."A Linear Quadratic Regulation Controller Based on Radial Basis Function Network Approximation".Electronics 13.21(2024):4279-4294.

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