This technical note presents a novel extremum seeking (ES)-based algorithm for global stabilization of unstable first order linear discrete-time (LDT) stochastic systems with unknown control directions. The probing signal is a martingale difference sequence with a vanishing variance. The controller parameter estimate converges almost surely (a.s.) to the optimizing value. The sample mean-square value of the output converges (a.s.) to the minimal variance.
['Miloje S. Radenkovic', 'Tom Altman']
Stochastic Adaptive Stabilization via Extremum Seeking in Case of Unknown Control Directions