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2008

On input-to-state stability of min-max nonlinear model predictive control

11 years 9 months ago
On input-to-state stability of min-max nonlinear model predictive control
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 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. Then, we derive new sufficient conditions that guarantee input-to-state stability of the min-max MPC closed-loop system, via a dual-mode approach. An illustrative example is also presented. Key words: Min-max, Nonlinear model predictive control, Input-to-state stability
Mircea Lazar, David Muñoz de la Peña
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where SCL
Authors Mircea Lazar, David Muñoz de la Peña, W. P. M. H. Heemels, Teodoro Alamo
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