Novel Adaptive Extended State Observer for Dynamic Parameter Identification with Asymptotic Convergence
[ 1 ] Instytut Automatyki i Robotyki, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ P ] employee
[2.2] Automation, electronics, electrical engineering and space technology
2022
scientific article
english
- parameter identification
- extended state observer
- persistent excitation
- Lyapunov stability
EN In this paper, a novel method of parameter identification of linear in parameter dynamic systems is presented. The proposed scheme employs an Extended State Observer to online estimate a state of the plant and momentary value of total disturbance present in the system. A notion is made that for properly redefined dynamics of the system, this estimate can be interpreted as a measure of modeling error caused by the parameter uncertainty. Under this notion, a disturbance estimate is used as a basis for classic gradient identification. A global convergence of both state and parameter estimates to their true values is proved using the Lyapunov approach under an assumption of a persistent excitation. Finally, results of simulation and experiments are presented to support the theoretical analysis. The experiments were conducted using a compliant manipulator joint and obtained results show the usefulness of the proposed method in drive control systems and robotics.
14.05.2022
3602-1 - 3602-22
Article Number: 3602
CC BY (attribution alone)
open journal
final published version
at the time of publication
public
140
3,2