Brief paper: Parameter convergence and minimal internal model with an adaptive output regulation problem

Authors:
Lu Liu;Zhiyong Chen;Jie Huang
Affiliations:
Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong;School of Electrical Engineering and Computer Science, The University of Newcastle, Callaghan, NSW 2308, Australia;Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Venue:
Automatica (Journal of IFAC)
Year:
2009

Citing 4
Cited 2

Stable adaptive systems

Stable adaptive systems
Nonlinear control design: geometric, adaptive and robust

Nonlinear control design: geometric, adaptive and robust
A New Approach to Adaptive Nonlinear Regulation

SIAM Journal on Control and Optimization
Global stabilization and disturbance suppression of a class of nonlinear systems with uncertain internal model

Automatica (Journal of IFAC)

Robust adaptive control of a class of nonlinear systems and its applications

IEEE Transactions on Circuits and Systems Part I: Regular Papers
Nonlinear output regulation with adaptive conditional servocompensator

Automatica (Journal of IFAC)

Quantified Score

Hi-index	22.15

Visualization

Abstract

The parameter convergence of nonlinear adaptive control systems is an important yet not well addressed issue. In this paper, using the global robust output regulation problem of output feedback systems with unknown exosystems as a platform, we will show that the well known persistency of excitation (PE) condition still guarantees the convergence of the estimated parameter vector to the true parameter vector. Moreover, the PE condition will be satisfied if the internal model is minimal in certain sense.