H-infinity prediction and unconstrained H-infinity predictive control: Multi-input-multi-output case

Citation
Hp. Zhao et al., H-infinity prediction and unconstrained H-infinity predictive control: Multi-input-multi-output case, INT J ROBUS, 11(1), 2001, pp. 59-86
Citations number
22
Language
INGLESE
art.tipo
Article
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
ISSN journal
1049-8923 → ACNP
Volume
11
Issue
1
Year of publication
2001
Pages
59 - 86
Database
ISI
SICI code
1049-8923(200101)11:1<59:HPAUHP>2.0.ZU;2-3
Abstract
Through the combination of the sequential spectral factorization and the co prime factorization, a k-step ahead MIMO H-infinity (cumulative minimax) pr edictor is derived which is stable for the unstable noise model. This predi ctor and the modified internal model of the reference signal are embedded i nto the H-infinity optimization framework, yielding a single degree of free dom multi-input-multi-output H-infinity predictive controller that provides stochastic disturbance rejection and asymptotic tracking of the reference signals described by the internal model. It is shown that for a plant/distu rbance model, that represents a large class of systems, the inclusion of th e H-infinity predictor into the H-infinity control algorithm introduces a p erformance/robustness tuning knob: an increase of the prediction horizon en forces a more conservative control effort and, correspondingly, results in deterioration of the transient and the steady-state (tracking error varianc e) performance, but guarantees large robustness margin, while the decrease of the prediction horizon results in a more aggressive control signal and b etter transient and steady-state performance, but smaller robustness margin . Copyright (C) 2001 John Wiley & Sons, Ltd.