Moses Won

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2023-245

December 1, 2023

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-245.pdf

We consider the stabilization of a discrete-time linear system in the presence of continuous multiplicative observation noise. Previous work has explored time-varying periodic non-linear control approaches for this problem. To understand the information-gathering role of control in this problem, this report explicitly computes how the conditional density of the state of the system evolves given the observations. The calculations suggest a novel control strategy that chooses the control equal to the maximum a-posteriori estimate for the state. We show that as n goes to infinity this control strategy does indeed drive the system state to 0 almost surely.

Advisors: Gireeja Ranade

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BibTeX citation:

@mastersthesis{Won:EECS-2023-245,
    Author= {Won, Moses},
    Title= {Distributional Interpretation of Control Strategies for a Multiplicative Observation Noise System},
    School= {EECS Department, University of California, Berkeley},
    Year= {2023},
    Month= {Dec},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-245.html},
    Number= {UCB/EECS-2023-245},
    Abstract= {We consider the stabilization of a discrete-time linear system in the presence of continuous multiplicative observation noise. Previous work has explored time-varying periodic non-linear control approaches for this problem. To understand the information-gathering role of control in this problem, this report explicitly computes how the conditional density of the state of the system evolves given the observations.
The calculations suggest a novel control strategy that chooses the control equal to the maximum a-posteriori estimate for the state. We show that as n goes to infinity this control strategy does indeed drive the system state to 0 almost surely.},
}

EndNote citation:

%0 Thesis
%A Won, Moses 
%T Distributional Interpretation of Control Strategies for a Multiplicative Observation Noise System
%I EECS Department, University of California, Berkeley
%D 2023
%8 December 1
%@ UCB/EECS-2023-245
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-245.html
%F Won:EECS-2023-245