Solutions to constrained linear model predictive control problems can be precomputed off-
line in an explicit form as a piecewise linear state feedback on a polyhedral partition of the …

This note describes a model predictive control (MPC) formulation for discrete-time linear
systems with hard constraints on control and state variables, under the assumption that the …

Explicit piecewise linear (PWL) state feedback laws solving constrained linear model
predictive control (MPC) problems can be obtained by solving multi-parametric quadratic …

This paper proposes a dual fast gradient-projection method for solving quadratic
programming problems that arise in model predictive control of linear systems subject to …

For discrete-time linear time-invariant systems with constraints on inputs and states, we
describe a method to determine explicitly, as a function of the initial state, the solution to …

A model predictive control law (MPC) is given by the solution to a parametric optimization
problem that can be precomputed offline, which provides an explicit map from state to input …

We show that explicit MPC solutions admit a closed-form solution which does not require the
storage of critical regions. Therefore significant amount of memory can be saved. In fact, not …

The practicality of model predictive control (MPC) is partially limited by its ability to solve
optimization problems in real time. Moreover, on-line computational demand for …

For discrete-time linear time-invariant systems with constraints on inputs and outputs, the
constrained finite-time optimal controller can be obtained explicitly as a piecewise-affine …

In this technical brief, we develop an algorithm to determine the explicit solution of the
constrained min-max model predictive control problem. For a discrete-time linear system …