Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Brief paper: Min-max MPC using a tractable QP problem
Automatica (Journal of IFAC)
An approach to fuzzy control of nonlinear systems: stability and design issues
IEEE Transactions on Fuzzy Systems
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
Quasi-Min-Max MPC algorithms for LPV systems
Automatica (Journal of IFAC)
Hi-index | 22.14 |
This paper studies the future model prediction and robust model predictive control (RMPC) design for linear parameter varying systems with bounded parameter changes. By developing tight bound estimations for varying parameters, we construct a set-valued map as the predicted family of future models. This construction attains accurate estimations and thus reduces conservativeness. Based on model predictions, we use a parameter-dependent feedback to design RMPC that achieves an enhanced performance with guaranteed robust and stability properties.