Sep 20, 2023 · We present a novel Model Predictive Control scheme that can guarantee recursive feasibility and/or safety under weaker assumptions than classic methods.

In this paper, we present a novel MPC scheme that ensures: i) safety, assuming the safe set is a conservative approximation of a specific backward reachable set ...

Aug 28, 2024 · As discussed above, a common way to ensure recursive feasibility in MPC is to constrain the final state inside a control-invariant set, such as ...

Aug 11, 2024 · This work proposes a novel controller design approach, and shows its recursive feasibility and stability. Moreover, the convergence of closed- ...

Aug 28, 2024 · Learning an approximate control-invariant set can significantly reduce the computational burden of MPC optimization while still ensuring safety.

Jun 15, 2024 · In this paper, a novel NMPC scheme based on -step control invariant sets is proposed. We employ symbolic control techniques to compute a -step control ...

Abstract—This paper presents a method to compute an approximate explicit model predictive control (MPC) law using neural networks. The optimal MPC control ...

Model predictive control (MPC) is an optimal-control based method to select control inputs by minimizing an objective function. The objective function.

Hence, the goal of this paper is to develop a framework for approximating a nonlinear MPC through supervised learning with statistical guarantees on stability ...

Model predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints.