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Ergodic Linear-Quadratic Optimal Control with Stochastic Coefficients

  • Xuyang Lin
  • Nizar Touzi
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Abstract

We investigate ergodic linear-quadratic optimal control problems with stochastic coefficients and introduce the associated stochastic ergodic Hamilton-Jacobi-Bellman (HJB) equation, in which the classical ergodic constant is replaced by a random process λ. We establish well-posedness of the equation and show that λ characterizes the optimal ergodic costs for a general class of averaging kernels, including those corresponding to normalized finite-horizon and discounted costs. For random-periodic coefficients, we construct a random-periodic solution and show that the optimal ergodic costs associated with all admissible averaging kernels coincide. We also establish stability of the optimal ergodic costs under perturbations of the coefficients.

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Cite

BibTeXRIS
BibTeX
@misc{lin2026ergodic,
  title = {{Ergodic Linear-Quadratic Optimal Control with Stochastic Coefficients}},
  author = {Xuyang Lin and Nizar Touzi},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.30219},
  eprint = {2610.30219},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.30219},
}
RIS
TY  - UNPB
TI  - Ergodic Linear-Quadratic Optimal Control with Stochastic Coefficients
AU  - Xuyang Lin
AU  - Nizar Touzi
PY  - 2026
DA  - 2026/10/21
PB  - arXiv
DO  - 10.48550/arxiv.2610.30219
UR  - https://arxiv.org/abs/2610.30219
AB  - We investigate ergodic linear-quadratic optimal control problems with stochastic coefficients and introduce the associated stochastic ergodic Hamilton-Jacobi-Bellman (HJB) equation, in which the classical ergodic constant is replaced by a random process λ. We establish well-posedness of the equation and show that λ characterizes the optimal ergodic costs for a general class of averaging kernels, including those corresponding to normalized finite-horizon and discounted costs. For random-periodic coefficients, we construct a random-periodic solution and show that the optimal ergodic costs associated with all admissible averaging kernels coincide. We also establish stability of the optimal ergodic costs under perturbations of the coefficients.
ER  -