Roche K.T.,Banner Health Corporation |
Rivera D.E.,Energy Control Systems Engineering |
Cochran J.K.,Air Force Institute of Technology
Mathematical and Computer Modelling | Year: 2012
As factors such as population growth, nation-wide closure of hospitals, and an aging population combine to strain the healthcare system of the United States (US), the demand for better resource and capacity planning increases. This paper proposes a five-step methodology to model and control whole hospital occupancy. The hospital system is viewed using a continuous-time, fluid tank analogy. The system is subsequently discretized and a framework using control theory and Model Predictive Control (MPC) is developed to assist in tactical decision making, while maintaining occupancy targets. The result is a customizable modeling approach that represents interactions between different hospital areas, and interactions between the hospital and the outside world, or the population seeking hospital services. © 2011 Elsevier Ltd.
Pavlovic T.,Energy Control Systems Engineering |
Bjazi T.,Polytechnic of Zagreb |
Ban Z.,Energy Control Systems Engineering
IEEE Transactions on Power Electronics | Year: 2013
This paper presents simplified nonlinear averaged large-signal and linear small-signal models of the three basic dc-dc converter topologies, boost, buck, and noninverting buck-boost, respectively, operating in peak current-mode control. Models have been derived for the continuous and discontinuous conduction mode. The modeling methodology used is the equivalent current injected method. The derived models have been compared to the existing full-order large-signal nonlinear models and have been found to exhibit simulation time reduction by a few magnitudes in complex distributed power systems, such as today's popular microgrids. The models developed have been experimentally verified on a custom-built 120-W boost converter prototype, showing great accuracy in steady state and in dynamical behavior in all operating points, as determined by the output resistance. © 1986-2012 IEEE.
PubMed | Energy Control Systems Engineering, Arizona State University and University of Alabama at Birmingham
Type: Journal Article | Journal: Translational behavioral medicine | Year: 2014
The term adaptive intervention has been used in behavioral medicine to describe operationalized and individually tailored strategies for prevention and treatment of chronic, relapsing disorders. Control systems engineering offers an attractive means for designing and implementing adaptive behavioral interventions that feature intensive measurement and frequent decision-making over time. This is illustrated in this paper for the case of a low-dose naltrexone treatment intervention for fibromyalgia. System identification methods from engineering are used to estimate dynamical models from daily diary reports completed by participants. These dynamical models then form part of a model predictive control algorithm which systematically decides on treatment dosages based on measurements obtained under real-life conditions involving noise, disturbances, and uncertainty. The effectiveness and implications of this approach for behavioral interventions (in general) and pain treatment (in particular) are demonstrated using informative simulations.
Abdelrahem M.,TU Munich |
Hackl C.M.,Energy Control Systems Engineering |
Kennel R.,TU Munich
Electrical Engineering | Year: 2016
This paper proposes a simplified finite-control-set model predictive current control (FCS-MPCC) without mechanical sensors for permanent-magnet synchronous generators (PMSGs) in variable-speed wind energy conversion systems. The procedure of selecting the best switching vector is optimized by computing the reference voltage vector (VV) directly from the reference current. Subsequently, the sector where this reference VV is located is determined from its angle. Finally, the cost function is evaluated only for three times to obtain the optimal switching vector. Therefore, the necessity to test all feasible VVs will be avoided, which reduces the calculation burden of the traditional finite-control-set model predictive control method. Moreover, an extended Kalman filter, which is a robust state observer, is proposed to estimate rotor speed, rotor position, and stator inductance of the PMSG. The estimated (filtered) stator currents, instead of the measured currents, are fed back to the prediction model, and therefore, a lower current total harmonic distortion and better noise rejection are realized. Estimation and control performance of the proposed simplified FCS-MPCC method are illustrated by the simulation results for all operation conditions. © 2016 Springer-Verlag Berlin Heidelberg
Varetsky Y.,AGH University of Science and Technology |
Pavlyshyn R.,Energy Control Systems Engineering |
Gajdzica M.,AGH University of Science and Technology
Przeglad Elektrotechniczny | Year: 2013
This paper focuses on the features of power filter switching-off in industrial power supply systems. The filter switching-off behavior under a large amount of a harmonic current component has been analyzed. The effect of harmonic current content in interrupting current, filter order tuning and switching condition are considered in the analysis. Finally, several oscillograms of simulated cases are included to show main points of the investigation.
PubMed | Arizona State University and Energy Control Systems Engineering
Type: Journal Article | Journal: IEEE transactions on control systems technology : a publication of the IEEE Control Systems Society | Year: 2013
We consider an improved model predictive control (MPC) formulation for linear hybrid systems described by mixed logical dynamical (MLD) models. The algorithm relies on a multiple-degree-of-freedom parametrization that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed-loop system. Consequently, controller tuning is more flexible and intuitive than relying on objective function weights (such as move suppression) traditionally used in MPC schemes. The controller formulation is motivated by the needs of non-traditional control applications that are suitably described by hybrid production-inventory systems. Two applications are considered in this paper: adaptive, time-varying interventions in behavioral health, and inventory management in supply chains under conditions of limited capacity. In the adaptive intervention application, a hypothetical intervention inspired by the
Taniguchi T.,Energy Control Systems Engineering
Hitachi Review | Year: 2013
As society moves towards a low-carbon future, the adoption of renewable energy and the utilization of previously untapped energy sources have grown in importance along with ongoing improvements in energy efficiency at manufacturing plants. Meanwhile, compliance with host countly regulations and coordination with the local community are also important factors for plant construction. Hitachi supplies factoiy and community energy-saving system solutions for a low-carbon society. © Hitachi, Ltd. 1994, 2013.
Energy Control Systems Engineering | Entity website
Energy Control Systems Engineering | Entity website
As global energy demands continue to rise exponentially, its become very apparent that renewable energy sources need to replace oil, coal, and other dirty, non-renewable sources. At some point, the damage to the environment will become irreversible and production wont be able to continue to meet demands if they continue to rise as they currently are ...