Adaptive systems in control and signal processing, 1998: a proceedings volume from the IFAC Workshop, Glasgow, Scotland, UK, 26-28 August 1998
Robert R. Bitmead, Michael A. Johnson, Michael J. Grimble, International Federation of Automatic Control
Pergamon, Feb 11, 2000 - Technology & Engineering - 482 pages
Adaptive Systems have been studied for a substantial period as the logical intersection between modelling and design in control and signal processing. Because of this, adaptive systems studies need to live in these two worlds while introducing concepts of their own. These reflect the requirements to track significant system variations or to eliminate initial parameter uncertainty, all the while maintaining satisfactory transient performance.
Historically, Adaptive Systems (and notably Adaptive Control) have been the subject of takeover bids by neighbouring tribes from fields such as gain-scheduling, identification, robust design or nonlinear systems. The response to this has been to add impetus to the understanding of the connections between these disciplines and adaptation, leading in turn to improvements of theory and practice. We would appear to be currently in a period where there are increasing contacts being made with fields such as Learning Systems, Computer Architectures and Identification. Rather than hostile takeovers, these have helped to expand the capability of Adaptive systems dramatically.
In this IFAC Workshop on Adaptive control and Signal Processing, a wide range of papers expressing the large number of fronts on which adaptive systems are developing has been drawn together.
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Uncertainty Model Unfalsification for Robust Adaptive Control
Analysis of Suboptimal Dual Control
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1998 IFAC Keywords adaptive control adaptive law algorithm application approximation ASOD assumed assumption Astrom Automatica basis functions beamformer bounded closed loop closed-loop system computed considered constant control algorithm Control and Signal control design control input control law control scheme control system controller parameters convergence Copyright cost function covariance matrix defined denotes Diophantine equation discrete-time disturbance dual control feedback feedback linearization feedforward filter FPGA frequency furnace fuzzy given IEEE IEEE Trans IFAC Adaptive Systems implementation iterative Kalman filter method minimal noise nonlinear systems obtained optimal output paper parameter estimation performance PID controller plant polynomial predictive control problem Proc proposed recursive recursive least squares reference model response sampling self-tuning sequence shown Signal Processing simulation Simulink stability step response stochastic structure system identification Systems in Control temperature Theorem time-varying tion tracking error transfer function trol tuning uncertainty unknown update variable vector Wittenmark zero