The classical theory of linear matrix inequality (LMI)-based linear quadratic regulator (LQR)
control that is well established in literature does not provide, in the controller project phase …

Model predictive control (MPC) represents nowadays one of the main methods employed for
process control in industry. Its strong suits comprise a simple algorithm based on a …

This paper is concerned with the robust H∞ model predictive control problem for a class of
non-linear systems subject to state and input constraints and with norm bounded …

Abstract Model Predictive Control (MPC) is the principal control technique used in industrial
applications. Although it offers distinguishable qualities that make it ideal for industrial …

A robust model predictive control (RMPC) framework is proposed for nonlinear cyber-
physical systems (CPSs) with input saturation and energy-bounded disturbance in this …

In this study, the authors address the problem of the mixed H2/H∞ robust model predictive
control (RMPC) for a class of discrete-time systems with structured uncertainty and …

A novel approach to the design of a less conservative model predictive control is proposed,
using mixed ℋ2/ℋ∞ design method for time-invariant discrete-time linear systems. The …

Uncertain constrained discrete‐time linear system is addressed using linear matrix
inequality based optimization techniques. The constraints on the inputs and states are …

A principal contribuição dessa tese é propor a representação H2/H∞ do regulador linear
quadrático (LQR) para sistemas lineares invariantes no tempo e incertos. A motivação está …

Uncertain constrained discrete-time linear system is addressed using linear matrix inequality
based optimization techniques. The constraints on the inputs and states are specified as …