It is well known that proportional output feedback control can stabilize any relative-degree one, minimum-phase system if the sign of the feedback is correct and the proportional gain is high enough. Moreover, there exists simple adaptation laws for tuning the proportional gain (the so-called high-gain adaptive controllers) which are not based on system identification or plant parameter estimation algorithms or injection of probing signals. If tracking of signals is desired, then these simple controllers are also applicable without invoking an internal model if the tracking error is not necessarily supposed to converge to zero but towards a ball around zero of arbitrarily small but prespecified radius λ>0. In this note we consider a sampled version of the high-gain adaptive λ-tracking controller. The motivation for sampling arises from the possibility that the output of a system may not be available continuously, but only at discrete time instants. The problem is that the stiffness of the system increases as the proportional gain is increased. Our result shows that adaptive sampling tracking is possible if the product hk of the decreasing sampling rate h and the increasing proportional gain k decreases at a rate proportional to 1/logk.
[1]
David H. Owens,et al.
Adaptive stabilization using a variable sampling rate
,
1996
.
[2]
Stuart Townley,et al.
Adaptive sampling control of high-gain stabilizable systems
,
1999,
IEEE Trans. Autom. Control..
[3]
J. Willems,et al.
Global adaptive stabilization in the absence of information on the sign of the high frequency gain
,
1984
.
[4]
Iven Mareels,et al.
A simple selftuning controller for stably invertible systems
,
1984
.
[5]
Achim Ilchmann,et al.
Non-identifier-based adaptive control of dynamical systems: a survey
,
1991
.
[6]
Stuart Townley,et al.
Adaptive control of infinite-dimensional systems without parameter estimation: an overview
,
1997
.
[7]
Achim Ilchmann,et al.
Non-Identifier-Based High-Gain Adaptive Control
,
1993
.
[8]
Eugene P. Ryan,et al.
Universal λ-tracking for nonlinearly-perturbed systems in the presence of noise
,
1994,
Autom..
[9]
Daniel E. Miller,et al.
An adaptive controller which provides an arbitrarily good transient and steady-state response
,
1991
.