Title :
On a Property of a Class of Offset-Free Model Predictive Controllers
Author :
Bageshwar, Vibhor L. ; Borrelli, Francesco
Author_Institution :
Dept. of Aerosp. Eng. & Mech., Univ. of Minnesota, Minneapolis, MN
fDate :
3/1/2009 12:00:00 AM
Abstract :
We consider a model predictive control framework that includes a discrete-time linear time-invariant nominal plant model augmented with an output integrator disturbance model and a Kalman filter to estimate the state and disturbance vectors. While the application of this framework can guarantee offset-free control, it has shown a consistent limitation in the achievable closed loop estimator performance. Using root locus techniques, we identify sufficient conditions for a class of nominal plant models with at least one real pole for which the closed loop estimator poles cannot be arbitrarily selected regardless of the augmented system´s statistics. We present several examples illustrating the limitations of the closed loop estimator pole locations.
Keywords :
Kalman filters; discrete time systems; predictive control; Kalman filter; closed loop estimator; discrete-time linear time-invariant model; disturbance vectors; offset-free control; offset-free model predictive controllers; root locus techniques; Observability; Performance analysis; Predictive control; Predictive models; State estimation; Statistics; Steady-state; Sufficient conditions; Uncertainty; Vectors; Chang Letov design; Kalman filter; disturbance models; model predictive control (MPC); root locus;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2009.2012998