System identification using a retrospective correction filter for adaptive feedback model updating

Authors:
M. A. Santillo;A. M. D'Amato;D. S. Bernstein
Affiliations:
Department of Aerospace Engineering, The University of Michigan, Ann Arbor, MI;Department of Aerospace Engineering, The University of Michigan, Ann Arbor, MI;Department of Aerospace Engineering, The University of Michigan, Ann Arbor, MI
Venue:
ACC'09 Proceedings of the 2009 conference on American Control Conference
Year:
2009

Citing 6
Cited 0

Adaptive control: stability, convergence, and robustness

Adaptive control: stability, convergence, and robustness
Stable adaptive systems

Stable adaptive systems
Applied system identification

Applied system identification
Robust adaptive control

Robust adaptive control
System identification (2nd ed.): theory for the user

System identification (2nd ed.): theory for the user
Brief A controller perturbation technique for transferring closed-loop stability between systems

Automatica (Journal of IFAC)

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we use a retrospective correction filter (RCF) to identify MIMO LTI systems. This method uses an adaptive controller in feedback with an initial model. The goal is to adapt the closed-loop response of the system to match the response of an unknown plant to a known input. We demonstrate this method on numerical examples of increasing complexity where the initial model is taken to be a one-step delay. Minimum-phase and nonminimum-phase SISO and MIMO examples are considered. The identification signals used include zero-mean Gaussian white noise as well as sums of sinusoids. Finally, we examine the robustness of this method by identifying these systems in the presence of actuator noise.