Matrix Inequalities Based Robust Model Predictive Control for Vehicle Considering Model Uncertainties and External Disturbances*

2020 ◽  
Author(s):  
Wenjun Liu ◽  
Guang Chen ◽  
Alois Knoll
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Matrix Inequalities ◽  
Model Uncertainties ◽  
External Disturbances ◽  
Robust Model Predictive Control ◽  
Robust Model

scholarly journals Robust Model Predictive Control Using Linear Matrix Inequalities for the Treatment of Asymmetric Output Constraints

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
Mariana Santos Matos Cavalca ◽  
Roberto Kawakami Harrop Galvão ◽  
Takashi Yoneyama
Keyword(s):  
Model Predictive Control ◽  
Linear Matrix Inequalities ◽  
Predictive Control ◽  
Constraint Satisfaction ◽  
Linear Matrix ◽  
Matrix Inequalities ◽  
Robust Model Predictive Control ◽  
Robust Model ◽  
Output Constraints

One of the main advantages of predictive control approaches is the capability of dealing explicitly with constraints on the manipulated and output variables. However, if the predictive control formulation does not consider model uncertainties, then the constraint satisfaction may be compromised. A solution for this inconvenience is to use robust model predictive control (RMPC) strategies based on linear matrix inequalities (LMIs). However, LMI-based RMPC formulations typically consider only symmetric constraints. This paper proposes a method based on pseudoreferences to treat asymmetric output constraints in integrating SISO systems. Such technique guarantees robust constraint satisfaction and convergence of the state to the desired equilibrium point. A case study using numerical simulation indicates that satisfactory results can be achieved.

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