Convergence of Self-Tuning Regulators under Conditional Heteroscedastic Noises with Unknown High-Frequency Gain

doi:10.1007/s11424-020-9117-9

CSpace

	Convergence of Self-Tuning Regulators under Conditional Heteroscedastic Noises with Unknown High-Frequency Gain
	Zhang, Yaqi; Guo, Lei
	2020-11-07
发表期刊	JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY
ISSN	1009-6124
页码	15
摘要	In the classical theory of self-tuning regulators, it always requires that the conditional variances of the systems noises are bounded. However, such a requirement may not be satisfied when modeling many practical systems, and one significant example is the well-known ARCH (autoregressive conditional heteroscedasticity) model in econometrics. The aim of this paper is to consider self-tuning regulators of linear stochastic systems with both unknown parameters and conditional heteroscedastic noises, where the adaptive controller will be designed based on both the weighted least-squares algorithm and the certainty equivalence principle. The authors will show that under some natural conditions on the system structure and the noises with unbounded conditional variances, the closed-loop adaptive control system will be globally stable and the tracking error will be asymptotically optimal. Thus, this paper provides a significant extension of the classical theory on self-tuning regulators with expanded applicability.
关键词	ARCH model conditional heteroscedasticity convergence self-tuning regulator weighted least-squares algorithm
DOI	10.1007/s11424-020-9117-9
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[11688101]
WOS研究方向	Mathematics
WOS类目	Mathematics, Interdisciplinary Applications
WOS记录号	WOS:000587281000026
出版者	SPRINGER HEIDELBERG
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/52468
专题	中国科学院数学与系统科学研究院
通讯作者	Zhang, Yaqi
作者单位	Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yaqi,Guo, Lei. Convergence of Self-Tuning Regulators under Conditional Heteroscedastic Noises with Unknown High-Frequency Gain[J]. JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,2020:15.
APA	Zhang, Yaqi,&Guo, Lei.(2020).Convergence of Self-Tuning Regulators under Conditional Heteroscedastic Noises with Unknown High-Frequency Gain.JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,15.
MLA	Zhang, Yaqi,et al."Convergence of Self-Tuning Regulators under Conditional Heteroscedastic Noises with Unknown High-Frequency Gain".JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY (2020):15.