Journal of Optimization Theory and Applications
Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Discrete-time stability with perturbations: application to model predictive control
Automatica (Journal of IFAC)
Worst-case formulations of model predictive control for systems with bounded parameters
Automatica (Journal of IFAC)
Robust time-optimal control of constrained linear systems
Automatica (Journal of IFAC)
Technical communique: Improving off-line approach to robust MPC based-on nominal performance cost
Automatica (Journal of IFAC)
Robustly asymptotically stable finite-horizon MPC
Automatica (Journal of IFAC)
Robust MPC of constrained discrete-time nonlinear systems based on approximated reachable sets
Automatica (Journal of IFAC)
Survey Constrained model predictive control: Stability and optimality
Automatica (Journal of IFAC)
The explicit linear quadratic regulator for constrained systems
Automatica (Journal of IFAC)
Optimization over state feedback policies for robust control with constraints
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Constrained RHC for LPV systems with bounded rates of parameter variations
Automatica (Journal of IFAC)
More efficient predictive control
Automatica (Journal of IFAC)
Approximate explicit receding horizon control of constrained nonlinear systems
Automatica (Journal of IFAC)
Robust constrained predictive control of uncertain norm-bounded linear systems
Automatica (Journal of IFAC)
Robust model predictive control using tubes
Automatica (Journal of IFAC)
Approximate robust dynamic programming and robustly stable MPC
Automatica (Journal of IFAC)
On the minimax reachability of target sets and target tubes
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
A fast ellipsoidal MPC scheme for discrete-time polytopic linear parameter varying systems
Automatica (Journal of IFAC)
Hi-index | 22.15 |
An off-line Model Predictive Control (MPC) method based on ellipsoidal calculus and viability theory is described in order to address control problems in the presence of state and input constraints for uncertain polytopic linear plants subject to persistent disturbances. In order to reduce the computational burdens and conservativeness of traditional polytopic MPC schemes, the present approach carries out off-line most of the computations and it makes use of closed-loop predictions to improve the control performance. This is done by recursively pre-computing suitable ellipsoidal inner approximations of the exact controllable sets and solving on-line a simple and numerically low-demanding optimization problem subject to a set-membership constraint. Comparisons with three other recent off-line MPC approaches are also provided in the final example.