Adaptive tracking of a class of first-order systems with binary-valued observations and fixed thresholds

CSpace

	Adaptive tracking of a class of first-order systems with binary-valued observations and fixed thresholds
其他题名	ADAPTIVE TRACKING OF A CLASS OF FIRST-ORDER SYSTEMS WITH BINARY-VALUED OBSERVATIONS AND FIXED THRESHOLDS
	Guo Jin; Zhang JiFeng; Zhao Yanlong
	2012-01-01
发表期刊	JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY
ISSN	1009-6124
卷号	25 期号:6 页码:1041-1051
摘要	This paper considers the adaptive tracking problem for a class of first-order systems with binary-valued observations generated via fixed thresholds. A recursive projection algorithm is proposed for parameter estimation based on the statistical properties of the system noise. Then, an adaptive control law is designed via the certainty equivalence principle. By use of the conditional expectations of the innovation and output prediction with respect to the estimates, the closed-loop system is shown to be stable and asymptotically optimal. Meanwhile, the parameter estimate is proved to be both almost surely and mean square convergent, and the convergence rate of the estimation error is also obtained. A numerical example is given to demonstrate the efficiency of the adaptive control law.
其他摘要	This paper considers the adaptive tracking problem for a class of first-order systems with binary-valued observations generated via fixed thresholds. A recursive projection algorithm is proposed for parameter estimation based on the statistical properties of the system noise. Then, an adaptive control law is designed via the certainty equivalence principle. By use of the conditional expectations of the innovation and output prediction with respect to the estimates, the closed-loop system is shown to be stable and asymptotically optimal. Meanwhile, the parameter estimate is proved to be both almost surely and mean square convergent, and the convergence rate of the estimation error is also obtained. A numerical example is given to demonstrate the efficiency of the adaptive control law
关键词	IDENTIFICATION Adaptive control binary-valued observation optimal tracking parameter estimation stochastic system
收录类别	CSCD
语种	英语
资助项目	[National Natural Science Foundation of China]
CSCD记录号	CSCD:4705674
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/52811
专题	中国科学院数学与系统科学研究院
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Guo Jin,Zhang JiFeng,Zhao Yanlong. Adaptive tracking of a class of first-order systems with binary-valued observations and fixed thresholds[J]. JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,2012,25(6):1041-1051.
APA	Guo Jin,Zhang JiFeng,&Zhao Yanlong.(2012).Adaptive tracking of a class of first-order systems with binary-valued observations and fixed thresholds.JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,25(6),1041-1051.
MLA	Guo Jin,et al."Adaptive tracking of a class of first-order systems with binary-valued observations and fixed thresholds".JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY 25.6(2012):1041-1051.