Model predictive control (MPC) is a popular control approach to ensure constraint
satisfaction, while minimizing a cost function. Although MPC usually leads to very good …

The systematic design of control laws for nonlinear systems subject to state and input
constraints is one of the major challenges in the control of realworld systems. Depending on …

This paper focuses on the constrained control of UAVs in geofencing applications. Although
geofence systems are becoming more attractive as a research topic, most works are …

This article provides a theory for provably safe and computationally efficient distributed
constrained control, and describes an application to a swarm of nano-quadrotors with limited …

Particle Swarm Optimization (PSO) is a numerical optimization technique based on the
motion of virtual particles within a multidimensional space. The particles explore the space …

In a cut-in scenario, traditional adaptive cruise control usually cannot effectively identify the
cut-in vehicle and respond to it in advance. This paper proposes an adaptive cruise control …

The explicit reference governor (ERG) is a simple and systematic approach that provides
constraint handling capabilities to prestabilized systems. The basic idea behind this …

This paper introduces a continuous-time constrained control strategy, which mimics the
behavior of a traditional model predictive control scheme using dynamic feedback. The …

In the linear system control, the traditional invariance-based explicit reference governor
(ERG) method provides a solution to the control of a class of systems subject to state and …

Active fault-tolerant control strategy aimed at tracking is studied for a class of discrete-time
Takagi-Sugeno (TS) fuzzy systems in the presence of input constraint and additive fault. In …