By
S. Bittanti, Dipartimento di Electtronica e Informazione, Politecnico di Milano, Italy
Description
In control and signal processing, adaptation is a natural tool to cope with real-time changes in the dynamical behaviour of signals and
systems. In this area, strongly connected with prediction and identification, there has been an increasing interest in switching and
supervising methods. Moreover in recent years, special attention has been paid to the ideas evolving round the theory of statistical
learning as a potential tool of improved adaptation.
The IFAC workshop on Adaptation and Learning in Control and Signal Processing
in 2001 gathered together experts in the field and interested researchers from universities and industry to present a full picture of
the area. This proceedings volume presents papers covering the following subjects: Model reference and predictive control; Multiple
model control; Adaptive control I/II; Adaptive control and learning; Learning; Adaptive control of nonlinear systems I/II; Supervisory
control; Neural networks for control; PID design methods; Sliding mode; Adaptive filtering and estimation; Identification methods I/II.
Included in series
IFAC Proceedings Volumes
Audience:
For experts and researchers in the field of signal processing.
