A New Algorithm for the LQR Problem with Partially Unknown Dynamics
Agnese Pacifico, Andrea Pesare, Maurizio Falcone
TL;DR
This paper introduces a novel online algorithm for solving the LQR optimal control problem when system dynamics are only partially known, enabling simultaneous learning and control in a single simulation.
Contribution
It presents a new model-based online method that estimates system dynamics and computes control simultaneously, advancing LQR solutions under uncertainty.
Findings
Effective in approximating unknown dynamics
Enables real-time control adaptation
Reduces need for extensive system identification
Abstract
We consider an LQR optimal control problem with partially unknown dynamics. We propose a new model-based online algorithm to obtain an approximation of the dynamics the control at the same time during a single simulation.
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Taxonomy
TopicsOptimization and Search Problems · Stability and Control of Uncertain Systems · Advanced Control Systems Optimization