We analyze properties of closed-loop systems based on explicit model predictive control (MPC) when parameters of the controllers are changing. Formulation of the problem in the framework of MPC with a cost based on piecewise linear norms leads to the generalized multi-parametric linear program containing parameters both in the cost and in the constraints. The focus of the paper is on describing a novel simplex-based algorithm for solving such a class of problems. The algorithm uses the concept of lexicographic perturbation to resolve problems caused by degenerac
In this paper, linear model predictive control problems are formulated as multi-parametric quadratic...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
Algorithms for solving multiparametric quadratic programming (MPQP) were recently proposed in Refs. ...
Abstract Optimal control problems for constrained linear systems with a linear cost can be posed as ...
Explicit solutions to constrained linear model predictive control problems can be obtained by solvin...
Abstract: Explicit piecewise linear (PWL) state feedback laws solving constrained linear model predi...
A standard model predictive controller (MPC) can be written as a parametric optimization problem who...
This paper deals with the implementation of min-max model predictive control for constrained linear ...
This thesis discusses recent advances in a variety of areas in multi-parametric programming and exp...
Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twe...
In this paper we introduce a new stage cost and show that the use of this cost allows one to formula...
This thesis is concerned with different topics in multi-parametric programming and explicit model pr...
The explicit solution of multi-parametric optimisation problems (MPOP) has been used to construct an...
The thesis is mainly focused on issues involved with explicit model predictive control approaches. C...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
In this paper, linear model predictive control problems are formulated as multi-parametric quadratic...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
Algorithms for solving multiparametric quadratic programming (MPQP) were recently proposed in Refs. ...
Abstract Optimal control problems for constrained linear systems with a linear cost can be posed as ...
Explicit solutions to constrained linear model predictive control problems can be obtained by solvin...
Abstract: Explicit piecewise linear (PWL) state feedback laws solving constrained linear model predi...
A standard model predictive controller (MPC) can be written as a parametric optimization problem who...
This paper deals with the implementation of min-max model predictive control for constrained linear ...
This thesis discusses recent advances in a variety of areas in multi-parametric programming and exp...
Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twe...
In this paper we introduce a new stage cost and show that the use of this cost allows one to formula...
This thesis is concerned with different topics in multi-parametric programming and explicit model pr...
The explicit solution of multi-parametric optimisation problems (MPOP) has been used to construct an...
The thesis is mainly focused on issues involved with explicit model predictive control approaches. C...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
In this paper, linear model predictive control problems are formulated as multi-parametric quadratic...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
Algorithms for solving multiparametric quadratic programming (MPQP) were recently proposed in Refs. ...