LQG solution for POMDP without estimating states: A minimum variance approach
Optimization and Control
2026-07-13 v1 Robotics
Systems and Control
Abstract
This paper investigates the control of discrete-time linear time-invariant (LTI) systems subject to incomplete and corrupted measurements. Specifically, we focus on designing a Linear Quadratic Gaussian (LQG) controller without relying on explicit state estimation. By leveraging minimum variance duality, our approach allows the current control input to be represented as a linear function of available measurements and previously applied inputs, successfully reducing the task to a tractable deterministic optimization problem. We provide theoretical justification for this framework and demonstrate its practical effectiveness through numerical experiments.
Cite
@article{arxiv.2607.12135,
title = {LQG solution for POMDP without estimating states: A minimum variance approach},
author = {Ranjan Sarkar and Prabhat K. Mishra},
journal= {arXiv preprint arXiv:2607.12135},
year = {2026}
}