Stabilizing model predictive control for LPV systems subject to constraints with parameter-dependent control law

2009 ◽  
Author(s):  
Shuyou Yu ◽  
Christoph Bohm ◽  
Hong Chen ◽  
Frank Allgower
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Law ◽  
Lpv Systems ◽  
Parameter Dependent

Model predictive control of constrained LPV systems

2012 ◽  
Vol 85 (6) ◽  
pp. 671-683 ◽  
Author(s):  
Shuyou Yu ◽  
Christoph Böhm ◽  
Hong Chen ◽  
Frank Allgöwer
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Lpv Systems

Model Predictive Control of Fractional Order Systems

2014 ◽  
Vol 9 (3) ◽  
Author(s):  
Aymen Rhouma ◽  
Faouzi Bouani ◽  
Badreddine Bouzouita ◽  
Mekki Ksouri
Keyword(s):  
Model Predictive Control ◽  
Dynamic Behavior ◽  
Fractional Order ◽  
Predictive Control ◽  
Internal Model ◽  
Direct Method ◽  
Control Law ◽  
Thermal System ◽  
Fractional Order Systems ◽  
Derivation Operator

This paper provides the model predictive control (MPC) of fractional order systems. The direct method will be used as internal model to predict the future dynamic behavior of the process, which is used to achieve the control law. This method is based on the Grünwald–Letnikov's definition that consists of replacing the noninteger derivation operator of the adopted system representation by a discrete approximation. The performances and the efficiency of this approach are illustrated with practical results on a thermal system and compared to the MPC based on the integer ARX model.

Robust multi-parametric model predictive control for LPV systems with application to anaesthesia

2014 ◽  
Vol 24 (10) ◽  
pp. 1538-1547 ◽  
Author(s):  
H. Chang ◽  
A. Krieger ◽  
A. Astolfi ◽  
E.N. Pistikopoulos
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Parametric Model ◽  
Lpv Systems

Actuator fault-tolerance evaluation of linear constrained model predictive control using zonotope-based set computations

2007 ◽  
Vol 221 (6) ◽  
pp. 915-926 ◽  
Author(s):  
C Ocampo-Martinez ◽  
P Guerra ◽  
V Puig ◽  
J Quevedo
Keyword(s):  
Fault Tolerance ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Admissible Solution ◽  
Control Law ◽  
Actuator Fault ◽  
Control Objective ◽  
Constrained Model ◽  
Constrained Model Predictive Control ◽  
Feasible Solutions

This paper presents a computational procedure to evaluate the fault tolerance of a linear-constrained model predictive control (LCMPC) scheme for a given actuator fault configuration (AFC). Faults in actuators cause changes in the constraints related to control signals (inputs), which in turn modify the set of MPC feasible solutions. This fact may result in an empty set of admissible solutions for a given control objective. Therefore, the admissibility of the control law facing actuator faults can be determined by knowing the set of feasible solutions. One of the aims of this paper is to provide methods to compute this set and to evaluate the admissibility of the control law for a given AFC, once the control objective and the admissibility criteria have been established. In particular, the admissible solution set for the predictive control problem, including the effect of faults (either through reconfiguration or accommodation), is determined using an algorithm that is implemented using set computations based on zonotopes. Finally, the proposed method is tested on a real application consisting of a part of the Barcelona sewer network.

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