Logarithm Laws of Self-tuning Regulators
[TMCSC]
July 24, 2018 15:30-16:30
W303 School of Mathematics, Sichuan University
SPEAKERS
李婵颖 (中国科学院数学与系统科学研究院)
ABSTRACT
It was demonstrated that in the Bayesian framework, the logarithm law generally characterizes the lower bound to the expected regret in regulation problems. For the Åström-Wittenmark STR problem, [Guo,1995] derived the precise convergence rate of the regret, which achieves the logarithm law exactly. This means the LS-STR is asymptotically efficient. We now prove that for nonlinear uncertain systems, the LS-STR, in some sense, still behaves theoretically superior to other adaptive controllers. The best possible convergence rate for the LS estimator and the logarithm law for regret can be obtained as well for nonlinear systems.
ORGANIZERS
Hui Kou (Sichuan University)
Xu Zhang (Sichuan University)
Jie Zhou (Sichuan University)
SUPPORTED BY
Tianyuan Mathematical Center in Southwest China
School of Mathematics, Sichuan University