Year: 2023
Type: preprint
Abstract: Although persistent excitation is often acknowledged as a sufficient condition to exponentially converge in the field of adaptive parameter estimation, it must be noted that in practical applications this may be unguaranteed. Recently, more attention has turned to another relaxed condition, i.e., finite excitation. In this paper, for a class of nominal nonlinear systems with unknown constant parameters, a novel method that combines the Newton algorithm and the time-varying factor is proposed, which can achieve exponential convergence under finite excitation. First, by introducing pre-filtering, the nominal system is transformed to a linear parameterized form. Then the detailed mathematical derivation is outlined from an estimation error accumulated cost function. And it is given that the theoretical analysis of the proposed method in stability and robustness. Finally, comparative numerical simulations are given to illustrate the superiority of the proposed method.
Source: arXiv (Cornell University)
Authors: Chen, Siyu, Na, Jing, Huang, Yingbo
Institution: Kunming University of Science and Technology
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4377864670