Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Constrained linear time-varying quadratic regulation with guaranteed optimality
International Journal of Systems Science
New formulation of robust MPC by incorporating off-line approach with on-line optimization
International Journal of Systems Science
Technical Communique: Superposition in efficient robust constrained predictive control
Automatica (Journal of IFAC)
Brief An improved approach for constrained robust model predictive control
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Hi-index | 0.00 |
This paper addresses robust MPC for constrained systems with polytopic uncertainty description. Firstly, in the technique which parameterizes the infinite horizon control moves into a single state feedback law and invokes the parameter-dependent Lyapunov method for achieving closed-loop stability, the slack matrices are iteratively solved at each sampling time. Secondly, in the technique which parameterizes the infinite horizon control moves into a set of free perturbations followed by a single state feedback law, the feedback gains within the switch horizon are iteratively found at each sampling time, rather than just inherited from the previous sampling time. Numerical examples show that iterative MPC can not only improve the control performance, but also enlarge the region of attraction.