Adaptive systems in control and signal processing, 1989: selected papers from the 3rd IFAC Symposium, Glasgow, UK, 19-21 April 1989, Volume 1989
Published for the International Federation of Automatic Control by Pergamon Press, 1990 - Technology & Engineering - 610 pages
The Symposium covered three major areas: adaptive control, identification and signal processing. In all three, new developments were discussed covering both theoretical and applications research. Within the subject area of adaptive control the discussion centred around the challenges of robust control design to unmodelled dynamics, robust parameter estimation and enhanced performance from the estimator, while the papers on identification took the theme of it being a bridge between adaptive control and signal processing. The final area looked at two aspects of signal processing: recursive estimation and adaptive filters.
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Adaptive Control Robustness and Performance Enhancement
E MOSCA J M LEMOS
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adaptive control adaptive control system applications approach assumed Astrom auto-tuner Automatica behaviour bounded closed loop system coefficients computational considered constant continuous-time control algorithm control input control law convergence defined denote discrete discrete-time disturbance equation error example Expert System feedback feedforward forgetting factor frequency gain given identification IEEE Trans implementation input signal Kalman filter least squares Lemma linear matrix measurement method minimize minimum phase model reference multivariable noise nonlinear obtained operator optimal control output paper parameter estimation performance phase PID control plant pole placement polynomial polynomial matrix predictive control predictor problem Proc properties recursive recursive least squares reference signal regulator response robust self-tuning control sequence set-point shown Signal Processing simulation solution stability stable polynomial step response stochastic structure Theorem time-varying tion tracking transfer function tuning unit circle variable variance vector white noise zero