@article{https://doi.org/10.1002/acs.3631,
author = {L'Afflitto, Andrea},
title = {Model reference adaptive control for nonlinear time-varying hybrid dynamical systems},
journal = {International Journal of Adaptive Control and Signal Processing},
volume = {37},
number = {8},
pages = {2162-2183},
keywords = {hybrid dynamical systems, LaSalle–Yoshizawa theorem, model reference adaptive control},
doi = {https://doi.org/10.1002/acs.3631},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/acs.3631},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/acs.3631},
abstract = {Summary This paper presents the first model reference adaptive control system for nonlinear, time-varying, hybrid dynamical plants affected by matched and parametric uncertainties, whose resetting events are unknown functions of time and the plant's state. In addition to a control law and an adaptive law, which resemble those of the classical model reference adaptive control framework for continuous-time dynamical systems, the proposed framework allows imposing instantaneous variations in the reference model's trajectory to rapidly steer the trajectory tracking error to zero, while retaining the closed-loop system's ability to follow a user-defined signal. These results are enabled by the first extension of the classical LaSalle–Yoshizawa theorem to time-varying hybrid dynamical systems, which is presented in this paper as well. A numerical simulation shows the key features of the proposed adaptive control system and highlights its ability to reduce both the control effort and the trajectory tracking error over a classical model reference adaptive control system applied to the same problem.},
year = {2023}
}