Stability and convergence analyses of an adaptive GPC based on state-space modeling
作者:
ABDEL-LATIF ELSHAFEI,
GUY DUMONT,
ASHRAF ELNAGGAR,
期刊:
International Journal of Control
(Taylor Available online 1995)
卷期:
Volume 61,
issue 1
页码: 193-210
ISSN:0020-7179
年代: 1995
DOI:10.1080/00207179508921898
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
A generalized predictive controller (GPC) is derived based on a general state-space model. The equivalence of the predictive control problem to a perturbation problem is revealed. In the case of a small perturbation, the closed-loop poles are calculated with high accuracy. For the case of a general perturbation, an upper bound on the permissible perturbation norm is derived assuming an open-loop stable system. Both the plant-model match and plant-model mismatch cases are analysed. The controller is proven to be robust and an adaptive implementation is motivated. For open-loop stable systems, the convergence and stability of the control scheme are ensured by proper tuning of the control weight and prediction horizon. The results are applicable to a wide range of predictive controllers. The main contribution of this paper is not a new control algorithm, but new techniques to analyse the GPC as well as new stability and convergence results.
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