Optimal control of continuous-time symmetric systems with unknown dynamics and noisy measurements
<|reference_start|>Optimal control of continuous-time symmetric systems with unknown dynamics and noisy measurements: An iterative learning algorithm is presented for continuous-time linear-quadratic optimal control problems where the system is externally symmetric with unknown dynamics. Both finite-horizon and infinite-horizon problems are considered. It is shown that the proposed algorithm is globally convergent to the optimal solution and has some advantages over adaptive dynamic programming, including being unbiased under noisy measurements and having a relatively low computational burden. Numerical experiments show the effectiveness of the results.<|reference_end|>
@article{taghavian2024optimal,
    title={Optimal control of continuous-time symmetric systems with unknown
  dynamics and noisy measurements},
    author={Hamed Taghavian, Florian Dorfler, Mikael Johansson},
    journal={arXiv preprint arXiv:2403.13605},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.13605},
    primaryClass={math.OC cs.SY eess.SY}
}