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Self-convergence of weighted least-squares with applications to stochastic adaptive control
Guo, L
1996
Source PublicationIEEE TRANSACTIONS ON AUTOMATIC CONTROL
ISSN0018-9286
Volume41Issue:1Pages:79-89
AbstractA recursive least-squares algorithm with slowly decreasing weights for linear stochastic systems is found to have self-convergence property, i.e., it converges to a certain random vector almost surely irrespective of the control law design, Such algorithms enjoy almost the same nice asymptotic properties as the standard least-squares. This ''universal convergence'' result combined with a method of random regularization then easily can be applied to construct a self-convergent and uniformly controllable estimated model and thus may enable us to form a general framework for adaptive control of possibly nonminimum phase autoregressive-moving average with exogenous input (ARMAX) systems, As an application, we give a simple solution to the well-known stochastic adaptive pole-placement and linear-quadratic-Gaussian (LQG) control problems in the paper.
Language英语
WOS Research AreaAutomation & Control Systems ; Engineering
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic
WOS IDWOS:A1996TQ67200007
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/28737
Collection中国科学院数学与系统科学研究院
AffiliationCHINESE ACAD SCI,INST SYST SCI,BEIJING 100080,PEOPLES R CHINA
Recommended Citation
GB/T 7714
Guo, L. Self-convergence of weighted least-squares with applications to stochastic adaptive control[J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL,1996,41(1):79-89.
APA Guo, L.(1996).Self-convergence of weighted least-squares with applications to stochastic adaptive control.IEEE TRANSACTIONS ON AUTOMATIC CONTROL,41(1),79-89.
MLA Guo, L."Self-convergence of weighted least-squares with applications to stochastic adaptive control".IEEE TRANSACTIONS ON AUTOMATIC CONTROL 41.1(1996):79-89.
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