The past three decades have witnessed important developments in the theory and practice of model predictive control (MPC). In particular, considerable effort has been devoted to robust MPC theory. There have also been many successful applications. This paper will give a brief overview of existing results and summarise experience gained in two real-world applications. We also present some reflections on issues which, in the authors’ opinion, deserve further attention
In model predictive control (MPC), also called recedinghorizon control, the control input is obtaine...
Most practical control problems are dominated by constraints. Although a rich theory has been develo...
Model Predictive Control (MPC) repeatedly solves a finite horizon optimal control problem subject to...
This paper gives an overview of robustness in Model Predictive Control (MPC). After reviewing the ba...
Model Predictive Control (MPC) usually refers to a class of control algorithms in which a dynamic pr...
Model predictive control (MPC) is a well-established modern control technology used in diverse appli...
[EN] In this work we are going to talk about the control algorithms. To explain this topic, first, w...
Model predictive control (MPC) is an advanced control design used in many industries worldwide. An M...
Frontiers of Model Predictive Control Robust Model Predictive Control Nonlinear Model Predictive Con...
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process mo...
In this paper, we discuss the model predictive control algorithms that are tailored for uncertain sy...
Controlling a system and state constraints is one of the most important problems in control theory, ...
Model Predictive Control (MPC) is a well-established technology for advanced control of many industr...
This thesis introduces a new interpretation of the problems arising in robust model predictive contr...
Model Predictive Control (MPC) is used to solve challenging multivariable-constrained control proble...
In model predictive control (MPC), also called recedinghorizon control, the control input is obtaine...
Most practical control problems are dominated by constraints. Although a rich theory has been develo...
Model Predictive Control (MPC) repeatedly solves a finite horizon optimal control problem subject to...
This paper gives an overview of robustness in Model Predictive Control (MPC). After reviewing the ba...
Model Predictive Control (MPC) usually refers to a class of control algorithms in which a dynamic pr...
Model predictive control (MPC) is a well-established modern control technology used in diverse appli...
[EN] In this work we are going to talk about the control algorithms. To explain this topic, first, w...
Model predictive control (MPC) is an advanced control design used in many industries worldwide. An M...
Frontiers of Model Predictive Control Robust Model Predictive Control Nonlinear Model Predictive Con...
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process mo...
In this paper, we discuss the model predictive control algorithms that are tailored for uncertain sy...
Controlling a system and state constraints is one of the most important problems in control theory, ...
Model Predictive Control (MPC) is a well-established technology for advanced control of many industr...
This thesis introduces a new interpretation of the problems arising in robust model predictive contr...
Model Predictive Control (MPC) is used to solve challenging multivariable-constrained control proble...
In model predictive control (MPC), also called recedinghorizon control, the control input is obtaine...
Most practical control problems are dominated by constraints. Although a rich theory has been develo...
Model Predictive Control (MPC) repeatedly solves a finite horizon optimal control problem subject to...