Linear Reduced-Order Model Predictive Control

Stabilizing reduced order model predictive control for constrained linear systems

Abstract: This paper considers a stabilizing reduced order model predictive control for constrained linear discrete-time systems. By employing a system decomposition on the inputoutput function space, a reduced order model predictive control law, which guarantees closedloop stability and feasibility, is obtained from a low dimensional on-line optimization problem. Numerical examples are provide...

Model Based Predictive Control for Linear Systems

Linear Model Predictive Control via Multiparametric Programming

Linear systems with input, output, or state constraints are probably themost important class of systems in practice and the most studied as well. Although, a variety of control design methods have been developed for linear systems, it is widely accepted that stability and good performance for these systems, especially in the presence of constraints, is guaranteed with a nonlinear control law. T...

Linear offset-free Model Predictive Control

This work addresses the problem of offset-free Model Predictive Control (MPC) when tracking an asymptotically constant reference. In the first part, compact and intuitive conditions for offset-free MPC control are introduced by using the arguments of the internal model principle. In the second part, we study the case where the number of measured variables is larger than the number of tracked va...

Linear programming and model predictive control

The practicality of model predictive control (MPC) is partially limited by the ability to solve optimization problems in real time. This requirement limits the viability of MPC as a control strategy for large scale processes. One strategy for improving the computational performance is to formulate MPC using a linear program. While the linear programming formulation seems appealing from a numeri...