A robust constrained reference governor approach using linear matrix inequalities

Robust constrained model predictive control using linear matrix inequalities,

The primary disadvantage of current design techriiques for xriodel predictive control (MPC) is their inability to deal explicitly with plant model uncertainty. In this paper, we present a new approacli for robust MPC synthesis which allows explicit irlcorporation of the description of pla,nt uricertainty in the problem formulation. The uncertainty is expressed both in the time domain and the fr...

Adaptive reference governor for constrained linear systems

This paper presents a novel adaptive reference governor for robust tracking control in constrained linear systems with bounded disturbances. The proposed reference governor achieves a performance improvement over the existing reference governors by virtue of its added feature: adaptability. The design of such an adaptive reference governor involves a nonlinear non-deterministic polynomial time ...

Robust Constrained Model Predictive Control by Linear Matrix Inequalities

Reference Governor for Constrained Piecewise Affine Systems

We present a methodology for designing reference tracking controllers for constrained, discrete-time piecewise affine systems. The approach follows the idea of reference governor techniques where the desired set-point is filtered by a system called the “reference governor”. Based on the system current state, set-point, and prescribed constraints, the reference governor computes a new set-point ...

Reference Governor for Constrained Nonlinear Systems

Reference Governor for Constrained Nonlinear Systems Alberto Bemporad Abstract| This note addresses the problem of satisfying pointwise-in-time input and/or state hard constraints in nonlinear control systems. The approach is based on conceptual tools of predictive control and consists of adding to a primal compensated nonlinear system a Reference Governor (RG). This is a discrete-time device w...