This work presents a Nonlinear Model Predictive Control (NMPC) scheme to perform evasive maneuvers and avoid rear-end collisions. Rear-end collisions are among the most common road fatalities. To reduce risk of collision, it is necessary for controller react as quickly possible exploit full vehicle maneuverability (i.e., combined control longitudinal lateral dynamics). The proposed design relie...

We present a model predictive control (MPC) framework to solve the constrained nonlinear output regulation problem. The main feature of proposed is that application does not require solution classical regulator (Francis-Byrnes-Isidori) equations or any other offline design procedure. In particular, formulation simply minimizes predicted error, possibly with some input regularization. Instead us...

the control of car following is essential due to its safety and its operational efficiency. for this purpose, this paper builds a model of car following behavior based on armax structure from a real traffic dataset and design a model predictive control (mpc) system. based on the relative distance and relative acceleration of each instant, the mpc predicts the future behavior of the leader vehic...

The current flexibility of the energy market requires operating steam turbines that have challenging operation requirements such as variable conditions and higher number startups. This article proposes an advanced control system based on Nonlinear Model Predictive Control (NMPC) technique, which allows to speed up start-up increase produced while maintaining rotor stress a constraint variable. ...

a new fault tolerant controller (ftc) has been presented in this research by integrating a fault detection and diagnosis (fdd) mechanism in a nonlinear model predictive controller framework. the proposed fdd utilizes a multi-sensor data fusion (msdf) methodology to enhance its reliability and estimation accuracy. an augmented state-vector model is developed to incorporate the occurred sensor fa...