Abstract
Abstract—In this paper we consider discrete-time nonlinear
systems that are affected, possibly simultaneously,
by parametric uncertainties and disturbance inputs. The
min-max model predictive control (MPC) methodology is
employed to obtain a controller that robustly steers the state
of the system towards a desired equilibrium. The aim is to
provide a priori sufficient conditions for robust stability of
the resulting closed-loop system via the input-to-state stability
framework. First, we show that only input-to-state practical
stability can be ensured in general for perturbed nonlinear
systems in closed-loop with min-max MPC schemes and we
provide explicit bounds on the evolution of the closed-loop
system state. Then, we derive new sufficient conditions that
guarantee input-to-state stability of the min-max MPC closedloop
system, via a dual-mode approach.
Keywords—Min-max, Nonlinear model predictive control,
Input-to-state stability, Input-to-state practical stability
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 17th Symposium on Mathematical Theory of Networks and Systems(MTNS 2006), July 24-28, 2006, Kyoto, Japan, |
| Pages | 108-114 |
| Publication status | Published - 2006 |
| Event | 17th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2006) - Kyoto, Japan Duration: 24 Jul 2006 → 28 Jul 2006 Conference number: 17th |
Conference
| Conference | 17th International Symposium on Mathematical Theory of Networks and Systems (MTNS 2006) |
|---|---|
| Abbreviated title | MTNS 2006 |
| Country | Japan |
| City | Kyoto |
| Period | 24/07/06 → 28/07/06 |
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Cite this
Lazar, M., Munoz de la Pena, D., Heemels, W. P. M. H., & Alamo, T. (2006). Min-max nonlinear model predictive control with guaranteed input-to-state stability. In Proceedings of the 17th Symposium on Mathematical Theory of Networks and Systems(MTNS 2006), July 24-28, 2006, Kyoto, Japan, (pp. 108-114)