The Multi-Parametric Toolbox is a col- lection of algorithms for modeling, control, analysis, and deployment of constrained optimal controllers developed under Matlab. It features a powerful ge- ometric library that extends the application of the toolbox beyond optimal control to various problems arising in computational geometry. The new version 3.0 is a complete rewrite of the original toolbox with a more flexible structure that offers faster integration of new algorithms. The numerical side of the toolbox has been improved by adding interfaces to state of the art solvers and by incorporation of a new parametric solver that relies on solving linear-complementarity problems. The toolbox provides algorithms for design and implementation of ...
Multiobjective optimization plays an increasingly important role in modern applications, where sever...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
In this paper, linear model predictive control problems are formulated as multi-parametric quadratic...
We analyze properties of closed-loop systems based on explicit model predictive control (MPC) when p...
Model predictive control (MPC) solves a quadratic optimization problem to generate control law in ea...
Polyhedral operations play a central role in constrained control. One of the most fundamental operat...
A robust PID controller design toolbox for Matlab is presented in this paper. The design is based on...
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...
The thesis is mainly focused on issues involved with explicit model predictive control approaches. C...
The success of the real-world implementation of advanced control policies relies on the robustness o...
Explicit solutions to constrained linear model-predictive control (MPC) problems can be obtained by ...
Model predictive control provides the optimal operation for chemical processes by explicitly account...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
Selected Papers from the International Conference on Informatics in Control, Automation and Robotics...
Multiobjective optimization plays an increasingly important role in modern applications, where sever...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
In this paper, linear model predictive control problems are formulated as multi-parametric quadratic...
We analyze properties of closed-loop systems based on explicit model predictive control (MPC) when p...
Model predictive control (MPC) solves a quadratic optimization problem to generate control law in ea...
Polyhedral operations play a central role in constrained control. One of the most fundamental operat...
A robust PID controller design toolbox for Matlab is presented in this paper. The design is based on...
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...
The thesis is mainly focused on issues involved with explicit model predictive control approaches. C...
The success of the real-world implementation of advanced control policies relies on the robustness o...
Explicit solutions to constrained linear model-predictive control (MPC) problems can be obtained by ...
Model predictive control provides the optimal operation for chemical processes by explicitly account...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
Selected Papers from the International Conference on Informatics in Control, Automation and Robotics...
Multiobjective optimization plays an increasingly important role in modern applications, where sever...
International audienceThis paper is dealing with the receding horizon optimal control techniques hav...
In this paper, linear model predictive control problems are formulated as multi-parametric quadratic...