This work focuses on evaluating the potential of variable speed limits (VSLs) in a synthetic urban network to improve both environmental sustainability and traffic performance. The system is modeled using microscopic simulator SUMO, physical fuel consumption NOx emission model used assess vehicles’ energy efficiency. Speed are controlled through nonlinear predictive control (NMPC) approach, whi...

 An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

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 describes autonomous racing of RC race cars based on mathematical optimization. Using a dynamical model of the vehicle, control inputs are computed by receding horizon based controllers, where the objective is to maximize progress on the track subject to the requirement of staying on the track and avoiding opponents. Two different control formulations are presented. The first control...

The increased interest in electric vehicles (EVs) in the recent years has intrigued numerous research, on improving efficiency and reducing ownership costs of these vehicles. As the battery in EVs is the sole energy provider, it is exposed to degradation due to high peaks and rapid fluctuations in the power demanded by the driver. Therefore, integrating a supercapacitor (SC) pack into the energ...

In this work, we propose a sim2real method to transfer and adapt nonlinear model predictive controller (NMPC) from simulation the real target system based on executable digital twin (xDT). The xDT is high fidelity vehicle dynamics simulator, online in control parameter randomization learning process. parameters are adapted gradually improve performance deal with changing real-world environment....

As off-the-shelf (OTS) autopilots become more widely available and user-friendly and the drone market expands, safer, more efficient, and more complex motion planning and control will become necessary for fixed-wing aerial robotic platforms. Considering typical low-level attitude stabilization available on OTS flight controllers, this paper first develops an approach for modeling and identifica...

Existing middleware standards cater to the requirement of a broad range of distributed applications. However they do not provide real-time performance guarantees portable in many mission-critical distributed real-time and embedded (DRE) systems operated in open and unpredictable environments. H∞ optimal control theory addresses the issue of worst-case controller design for plants subjected to u...

In this article a stabilizing feedback control is computed for a semilinear parabolic partial differential equation utilizing a nonlinear model predictive (NMPC) method. In each level of the NMPC algorithm the finite time horizon open loop problem is solved by a reduced-order strategy based on proper orthogonal decomposition (POD). A stability analysis is derived for the combined PODNMPC algori...

The main objective of the presented work is to compare two model predictive control strategies by applying them to an antibiotic production in a fed-batch fermentation process. The reactor is modelled as a nonlinear biological compartment system with 13 states. The well-known nonlinear model predictive control (NMPC) is compared with a control strategy based on online optimization of the full t...