Fractional Calculus in Optimal Control and Game Theory: Theory, Numerics, and Applications -- A Survey

Fuente: arXiv
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Main Authors: Mojahed, Navid, Fatoorehchi, Hooman, Nazari, Shima
Format: Preprint
Published: 2025
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author Mojahed, Navid
Fatoorehchi, Hooman
Nazari, Shima
author_facet Mojahed, Navid
Fatoorehchi, Hooman
Nazari, Shima
contents Many physical, biological, and engineered systems exhibit memory effects that challenge Markovian models. Fractional calculus provides nonlocal operators to capture hereditary dynamics. This survey connects modeling, analysis, and controller/game design for systems with memory. We unify notation for Caputo, Riemann-Liouville, and Grunwald-Letnikov derivatives and relate them to practical approximations, including diffusive (sum-of-exponentials) state augmentation and frequency-domain realizations (e.g., Oustaloup). We review fractional extensions of the calculus of variations and the Pontryagin maximum principle, and dynamic-programming formulations with memory, including path-dependent HJB for optimal control and HJI for zero-sum games. We cover design tools such as LQR, MPC, and fractional-order PID, as well as fractional differential games with Nash, Stackelberg, and minimax equilibria. Computational approaches are compared across time-domain schemes, frequency-domain approximations, and diffusive augmentations, highlighting accuracy-complexity trade-offs and remedies for the curse of history (windowing and sum-of-exponentials). We conclude with applications and open problems on equilibria with memory, Isaacs-type conditions, constraint handling, and scalable solvers.
format Preprint
id arxiv_https___arxiv_org_abs_2512_12111
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Fractional Calculus in Optimal Control and Game Theory: Theory, Numerics, and Applications -- A Survey
Mojahed, Navid
Fatoorehchi, Hooman
Nazari, Shima
Optimization and Control
Systems and Control
49N70, 93C10, 93C55, 91A10, 34A08
Many physical, biological, and engineered systems exhibit memory effects that challenge Markovian models. Fractional calculus provides nonlocal operators to capture hereditary dynamics. This survey connects modeling, analysis, and controller/game design for systems with memory. We unify notation for Caputo, Riemann-Liouville, and Grunwald-Letnikov derivatives and relate them to practical approximations, including diffusive (sum-of-exponentials) state augmentation and frequency-domain realizations (e.g., Oustaloup). We review fractional extensions of the calculus of variations and the Pontryagin maximum principle, and dynamic-programming formulations with memory, including path-dependent HJB for optimal control and HJI for zero-sum games. We cover design tools such as LQR, MPC, and fractional-order PID, as well as fractional differential games with Nash, Stackelberg, and minimax equilibria. Computational approaches are compared across time-domain schemes, frequency-domain approximations, and diffusive augmentations, highlighting accuracy-complexity trade-offs and remedies for the curse of history (windowing and sum-of-exponentials). We conclude with applications and open problems on equilibria with memory, Isaacs-type conditions, constraint handling, and scalable solvers.
title Fractional Calculus in Optimal Control and Game Theory: Theory, Numerics, and Applications -- A Survey
topic Optimization and Control
Systems and Control
49N70, 93C10, 93C55, 91A10, 34A08
url https://arxiv.org/abs/2512.12111