Robust constrained model predictive control using linear matrix inequalities
Automatica (Journal of IFAC)
Worst-case formulations of model predictive control for systems with bounded parameters
Automatica (Journal of IFAC)
| Hi-index | 22.14 |
The problem of regulating an uncertain and/or time-varying linear discrete-time system with state and control constraints to the origin is addressed. It is shown that feasibility and a robustly asymptotically stable closed loop can be achieved using an interpolation technique. The design method can be seen as an alternative to optimization-based control schemes such as Robust Model Predictive Control. Especially for problems requiring complex calculations to find the optimal solution, the present method can provide a straightforward suboptimal solution. A simulation demonstrates the performance of this class of constrained controllers.