International audienceThis article addresses the fast on-line solution of a sequence of quadratic programs underlying a linear model predictive control scheme. We introduce an algorithm which is tailored to efficiently handle small to medium sized problems with relatively small number of active constraints. Different aspects of the algorithm are examined and its computational complexity is presented. Finally, we discuss a modification of the presented algorithm that produces "good" approximate solutions faster
A key component in enabling the application of model predictive control (MPC) in fields such as auto...
A model predictive control (MPC) strategy based on augmented autonomous predictions enables a highly...
In model predictive control (MPC) an optimization problem has to be solved at each time step, which ...
International audienceThis article addresses the fast on-line solution of a sequence of quadratic pr...
International audienceThis article addresses the fast solution of a Quadratic Program underlying a L...
Summary. This article addresses the fast on-line solution of a sequence of quadratic programs underl...
tion problem needs to be solved at each sampling time, and this has traditionally limited use of MPC...
Linear quadratic model predictive control (MPC) with input constraints leads to an optimization prob...
Nearly all algorithms for linear model predictive control (MPC) either rely on the solution of conve...
The last three decades have seen a rapidly increasing number of applications where model predictive ...
This thesis develops efficient optimization methods for Model Predictive Control (MPC) to enable its...
In this paper we review a dual fast gradient-projection approach to solving quadratic programming (Q...
Fast and efficient numerical methods for solving Quadratic Programming problems (QPs) in the area of...
Min–max model predictive controllers (MMMPC) suffer from a great computational burden that is often ...
Model predictive control (MPC) is computationally expensive, because it is based on solving an optim...
A key component in enabling the application of model predictive control (MPC) in fields such as auto...
A model predictive control (MPC) strategy based on augmented autonomous predictions enables a highly...
In model predictive control (MPC) an optimization problem has to be solved at each time step, which ...
International audienceThis article addresses the fast on-line solution of a sequence of quadratic pr...
International audienceThis article addresses the fast solution of a Quadratic Program underlying a L...
Summary. This article addresses the fast on-line solution of a sequence of quadratic programs underl...
tion problem needs to be solved at each sampling time, and this has traditionally limited use of MPC...
Linear quadratic model predictive control (MPC) with input constraints leads to an optimization prob...
Nearly all algorithms for linear model predictive control (MPC) either rely on the solution of conve...
The last three decades have seen a rapidly increasing number of applications where model predictive ...
This thesis develops efficient optimization methods for Model Predictive Control (MPC) to enable its...
In this paper we review a dual fast gradient-projection approach to solving quadratic programming (Q...
Fast and efficient numerical methods for solving Quadratic Programming problems (QPs) in the area of...
Min–max model predictive controllers (MMMPC) suffer from a great computational burden that is often ...
Model predictive control (MPC) is computationally expensive, because it is based on solving an optim...
A key component in enabling the application of model predictive control (MPC) in fields such as auto...
A model predictive control (MPC) strategy based on augmented autonomous predictions enables a highly...
In model predictive control (MPC) an optimization problem has to be solved at each time step, which ...