Pub. online:1 Jan 1993Type:Research ArticleOpen Access
Volume 4, Issues 1-2 (1993), pp. 3–20
Design problems of predictor-based self-tuning digital control systems for different kinds of linear and non-linear dynamical plants are discussed. Special cases include linear plants with unstable and nonminimum-phase control channels, linear plants with inner feedbacks, nonlinear Hammerstein and Wiener-Hammerstein-type plants. Considered are control systems based on generalized minimum variance algorithms with amplitude and introduction rate restrictions for the control signal.
Pub. online:1 Jan 1991Type:Research ArticleOpen Access
Volume 2, Issue 1 (1991), pp. 33–52
Self-tuning control with recursive identification of extremal dynamic systems is considered. The systems can be represented by combinations of linear dynamic and extremal static parts, their output being disturbed by a coloured noise. Minimum-variance controllers for Hammerstein, Wiener, and Wiener-Hammerstein-type systems are designed taking into consideration restrictions for control signal magnitude and/or change rate. The estimates of unknown parameters in the controller equations are obtained in the identification process in the closed loop. The efficiency of self-tuning control algorithms is illustrated by statistical simulation. On the basis of worked out methods, adaptive systems for optimization of fuel combustion and steam condensation processes in thermal power units are developed.