We propose an approximate explicit model predictive control (MPC) scheme based on ideas in robust MPC. For every subset in a partial partition of the state space we solve a robust MPC problem offline, where the (only) uncertainty is the initial condition which may be any state in this particular subset. As a consequence, the control law defined by the solution of the MPC problem is valid for any state in the subset. The online computational effort reduces to a point location problem and application of the pre-computed MPC solution
The thesis is mainly focused on issues involved with explicit model predictive control approaches. C...
In this paper, we present an off-line approach for robust constrained MPC synthesis that gives an ex...
Many robust model predictive control (MPC) schemes require the online solution of a computationally ...
We propose an approximate explicit model predictive control (MPC) scheme based on ideas in robust MP...
This article presents an algorithm for robust nonlinear explicit model predictive control. A low com...
A robust tube-based Model Predictive Control (MPC) strategy is proposed for linear systems with mult...
This paper develops a parameterized tube model predictive control (MPC) synthesis method. The most r...
An adaptive Model Predictive Control (adaptive MPC) strategy is proposed for linear systems with con...
For linear systems with multiplicative uncertainty, a formulation of robust model predictive control...
Robust tube-based model predictive control (MPC) methods address constraint satisfaction by leveragi...
Reaching a sensible compromise between computational tractability and degree of optimality still rem...
Recently, a technical note [4] ensured recursive feasibility in robust model predictive control with...
Explicit model predictive control (MPC) addresses the problem of removing one of the main drawbacks ...
Model Predictive Control (MPC) repeatedly solves a finite horizon optimal control problem subject to...
International audienceThis article focuses on the design of a robust model predictive control law fo...
The thesis is mainly focused on issues involved with explicit model predictive control approaches. C...
In this paper, we present an off-line approach for robust constrained MPC synthesis that gives an ex...
Many robust model predictive control (MPC) schemes require the online solution of a computationally ...
We propose an approximate explicit model predictive control (MPC) scheme based on ideas in robust MP...
This article presents an algorithm for robust nonlinear explicit model predictive control. A low com...
A robust tube-based Model Predictive Control (MPC) strategy is proposed for linear systems with mult...
This paper develops a parameterized tube model predictive control (MPC) synthesis method. The most r...
An adaptive Model Predictive Control (adaptive MPC) strategy is proposed for linear systems with con...
For linear systems with multiplicative uncertainty, a formulation of robust model predictive control...
Robust tube-based model predictive control (MPC) methods address constraint satisfaction by leveragi...
Reaching a sensible compromise between computational tractability and degree of optimality still rem...
Recently, a technical note [4] ensured recursive feasibility in robust model predictive control with...
Explicit model predictive control (MPC) addresses the problem of removing one of the main drawbacks ...
Model Predictive Control (MPC) repeatedly solves a finite horizon optimal control problem subject to...
International audienceThis article focuses on the design of a robust model predictive control law fo...
The thesis is mainly focused on issues involved with explicit model predictive control approaches. C...
In this paper, we present an off-line approach for robust constrained MPC synthesis that gives an ex...
Many robust model predictive control (MPC) schemes require the online solution of a computationally ...