Transport, rescue, search, surveillance, and disaster relief tasks are some applications that can be developed with unmanned aerial vehicles (UAVs), where accurate trajectory tracking is a crucial property to operate in cluttered environment or under uncertainties. However, this challenging due high nonlinear dynamics, system constraints, uncertainties presented environments. Hence, the form of...

Modulation of the inflammatory response has become a key focal point in the treatment of critically ill patients. Much of the computational work in this emerging field has been carried out with the goal of unraveling the primary drivers, interconnections, and dynamics of systemic inflammation. To translate these theoretical efforts into clinical approaches, the proper biological targets and spe...

This paper tackles the regulation problem of wheeled mobile robot (WMR) by using the nonlinear model predictive control (NMPC) in polar coordination framework. The terminal state penalty, terminal state constraints, and the input saturation constraints are taken into consideration in this optimization problem to guarantee the closed-loop regulation performance and stability. Furthermore, we imp...

Model predictive control (MPC) anticipates future events to take appropriate control actions. Nonlinear MPC (NMPC) describes systems with nonlinear models and/or constraints. A Continuation/GMRES Method for NMPC, suggested by T. Ohtsuka in 2004, uses the GMRES iterative algorithm to solve a forward difference approximation Ax = b of the Continuation NMPC (CNMPC) equations on every time step. Th...

The recent widespread diffusion of Combined Cycle Power Plants (CCPPs) is due to crucial technological advantages with respect to oil or coal fired plants. Among them, CCPPs guarantee higher efficiency and lower emissions. However, in the context of a deregulated energy market, better performances of the CCPPs control schemes are required during load transitions to allow for their use in grid f...

High-speed parallel manipulators are characterized by fast sampling rates and challenges owing to the presence of constraints, high nonlinearities, uncertainties, dynamics. The development a reliable nonlinear model predictive control (NMPC) approach for this type robotic systems is challenging because complex dynamics that involves computational burden. To address problem, paper proposes new N...

This paper aims to solve the fault tolerant control problem of a wind turbine benchmark. A hierarchical controller with model predictive pre-compensators, a global model predictive controller and a supervisory controller is proposed. In the model predictive pre-compensator, an extended Kalman Filter is designed to estimate the system states and various fault parameters. Based on the estimation,...

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...

The paper deals with the problem of robust predictive fault-tolerant control for nonlinear discrete-time systems described by the Takagi-Sugeno models. The proposed approach consists of three steps, i.e. it starts from fault estimation, the fault is compensated with a robust controller, and finally, when the compensation is not successful then a suitable predictive action is performed. This app...