Finite-time convergence results in robust model predictive control

2018 ◽  
Vol 39 (5) ◽  
pp. 1627-1637 ◽  
Author(s):  
A. Anderson ◽  
A.H. González ◽  
A. Ferramosca ◽  
E. Kofman
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Finite Time ◽  
Robust Model Predictive Control ◽  
Finite Time Convergence ◽  
Robust Model ◽  
Convergence Results

Model Predictive Control with on-off Input and its Application to Attitude Control

2014 ◽  
Vol 898 ◽  
pp. 713-719
Author(s):  
Bao Qing Yang ◽  
Xi Zhang ◽  
Kai Ning Wu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Finite Time ◽  
Attitude Control ◽  
Decision Variable ◽  
Robust Model Predictive Control ◽  
Robust Model ◽  
Target Set ◽  
Simulation Results

Robust model predictive control with On-Off input of system is researched in this paper. The constraint tightening approach is adopted to ensure robustness of algorithm. By variable horizon approach, i.e. take the predictive horizon as the decision variable, the property of finite-time arrival within an arbitrary target set is guaranteed. Convergence of the algorithm is proved, and the maximum predictive horizon for the states entry to an arbitrary target set is determined. Finally, the method is applied to the attitude control of exo-atmospheric aerocraft, the simulation results show the effectiveness of the proposed method.

Robust model predictive control with zone control

2009 ◽  
Vol 3 (1) ◽  
pp. 121-135 ◽  
Author(s):  
A.H. González ◽  
D. Odloak ◽  
J.L. Marchetti
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Robust Model Predictive Control ◽  
Zone Control ◽  
Robust Model
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