Title: Experimental parameter estimation methodology based on equivalent output injection

Authors: David I. Rosas Almeida; Karla D. Espinoza Carballo; Karla I. Velazquez Victorica

Addresses: Faculty of Engineering, Universidad At´onoma de Baja California, Mexicali, Mexico ' Faculty of Engineering, Universidad At´onoma de Baja California, Mexicali, Mexico ' Faculty of Engineering, Universidad At´onoma de Baja California, Mexicali, Mexico

Abstract: This work proposes a methodology to estimate parameters for linear and nonlinear dynamical systems, with partial state measurement, that satisfy the property of parameter linearity. This methodology is experimental, offline, and recursive. It uses discontinuous state observers to estimate all state variables and the disturbance terms needed in the estimation processes. Because the equivalent output injection corresponds to the disturbances produced by the parameter uncertainties, the methodology allows us to obtain the best parameter estimation by minimising an index related to the power of the equivalent output injection; a smaller value represents a better estimation. With this parameter estimation, we can establish a model that facilitates the design and implementation of many control algorithms, including robust controllers. We validate the methodology through numerical simulations and experiments with linear, nonlinear, and discontinuous systems. Based on the experimental results, we conclude that the proposed algorithm's performance is better than other methodologies.

Keywords: identification; modelling; equivalent output injection; discontinuous observers; least squares algorithm.

DOI: 10.1504/IJMIC.2023.128769

International Journal of Modelling, Identification and Control, 2023 Vol.42 No.1, pp.4 - 16

Received: 07 Oct 2021
Accepted: 10 Feb 2022
Published online: 03 Feb 2023 *