@inproceedings{027cc49327544f1b8461eebd9616fecf,
title = "Robust path integral control on stochastic differential games",
abstract = "This paper develops a robust path integral (RPI) model predictive control using the Monte Carlo (MC) sampling to address the optimal control (OC) problem for the stochastic differential game (SDG). The two-player zero-sum differential game has been extensively investigated, mostly as its outcome indicates the H∞ optimality. The proposed path integral (PI) control framework provides an analytically sound method for building an algorithm of optimal control for this game based on stochastic trajectory sampling. This is achieved by using Feynman-Kac (F-K) lemma which transforms the value function of stochastic optimal control (SOC) problem into an expectation over all probable trajectories. This transformation makes it possible to solve SOC problems through MC sampling of stochastic processes. Finally, the RPI model predictive control using MC sampling is efficiently implemented for an inverted pendulum system. The RPI control has achieved good performance for changes in inverted pendulum weight and friction when the complete nonlinear swing-up is concerned while such environmental adjustments are not dealt with in a regular PI control.",
keywords = "Optimal control, Path integral, Robust control, Sampling, Stochastic differential games",
author = "D. Vrushabh and P. Akshay and K. Sonam and S. Wagh and Singh, {N. M.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 28th Mediterranean Conference on Control and Automation, MED 2020 ; Conference date: 15-09-2020 Through 18-09-2020",
year = "2020",
month = sep,
doi = "10.1109/MED48518.2020.9183351",
language = "English",
series = "2020 28th Mediterranean Conference on Control and Automation, MED 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "665--670",
booktitle = "2020 28th Mediterranean Conference on Control and Automation, MED 2020",
}