Title :
A systematic method to enhance the robustness of stabilising receding-horizon predictive controllers
Author :
Megias, D. ; Serrano, J. ; Kuznetsov, A.G.
Author_Institution :
Dept. d´Inf., Univ. Autonoma de Barcelona, Barcelona, Spain
fDate :
Aug. 31 1999-Sept. 3 1999
Abstract :
Although stability guarantees are available for predictive controllers, closed-loop instability may arise due to system uncertainty. The T-design and the Q-parametrisation methods are often used to enhance the robustness of predictive controllers. The former is heuristic, whereas optimisation rules exist for the latter, which makes it systematic. However, the T-design tends to producing larger robustness margins. The T-optimisation presented here is a systematic procedure to choose T based on optimising a quadratic criterion on robustness and thus, overcomes the drawbacks of heuristic approaches. This method can lead to robustness margins larger than those obtained with other techniques.
Keywords :
optimisation; predictive control; robust control; Q-parametrisation methods; T-design; T-optimisation; closed-loop instability; quadratic criterion; receding-horizon predictive controllers; system uncertainty; Optimization; Polynomials; Predictive control; Robustness; Stability analysis; Tuning; Uncertainty; predictive control; robustness; stability guarantees; uncertainty;
Conference_Titel :
Control Conference (ECC), 1999 European
Conference_Location :
Karlsruhe
Print_ISBN :
978-3-9524173-5-5