1,326 research outputs found
What is the Time Limit for Filing a Lawsuit? It Depends on What Your Definition of Arising Under Is! An Analysis of Jones v. R.R. Donnelley & Sons Co.
No full textThis article previews the Supreme Court case Jones et. al. v. R.R. Donnelly & Sons Co., 541 U.S. 369 (2004). The author predicted that the case would require the court to determine the appropriate statute of limitations to apply in a class action race-discrimination lawsuit filed under 42 U.S.C. § 1981
Dynamic synchromodal transport planning under uncertainty: A reinforcement learning approach
No full textAccepted Author ManuscriptTransport Engineering and Logistic
The Scope of Employer Liability for Employee Exposure to a Hazardous Substance: No Harm, No Foul? An Analysis of Metro-North Commuter R.R. Co. v. Buckley
No full textThis article previews the Supreme Court case Metro-North Commuter R.R. Co. v. Buckley, 521 U.S. 424 (1997). The author expected the Court to decide whether a railroad worker who is covered by the Federal Employer\u27s Liability Act who has been exposed to asbestos because of employer negligence but who has not developed an asbestos-related disease can recover damages for emotional distress caused by the exposure
Multi-agent model predictive control for transportation networks: Serial versus parallel schemes
No full textWe consider the control of large-scale transportation networks, like road traffic networks, power distribution networks, water distribution networks, etc. Control of these networks is often not possible from a single point by a single intelligent control agent; instead control has to be performed using multiple intelligent agents. We consider multi-agent control schemes in which each agent employs a model-based predictive control approach. Coordination between the agents is used to improve decision making. This coordination can be in the form of parallel or serial schemes. We propose a novel serial coordination scheme based on Lagrange theory and compare this with an existing parallel scheme. Experiments by means of simulations on a particular type of transportation network, viz., an electric power network, illustrate the performance of both schemes. It is shown that the serial scheme has preferable properties compared to the parallel scheme in terms of the convergence speed and the quality of the solution. If you want to cite this report, please use the following reference instead: R.R. Negenborn, B. De Schutter, and J. Hellendoorn, “Multi-agent model predictive control for transportation networks: Serial versus parallel schemes,” Engineering Applications of Artificial Intelligence, vol. 21, no. 3, pp. 353–366, Apr. 2008.Delft Center for Systems and ControlMechanical, Maritime and Materials Engineerin
Optimization of condition-based asset management using a predictive health model
No full textIn this paper, a model predictive framework is used to optimize the operation and maintenance actions of power system equipment based on the predicted health sate of this equipment. In particular, this framework is used to predict the health state of transformers based on their usage. The health state of a transformer is hereby given by the hot-spot temperature of the paper insulation of the transformer and is predicted using the planned loading of the transformer. The actual loading of the transformer is subsequently optimized using these predictions. If you want to cite this report, please use the following reference instead: G. Bajracharya, T. Koltunowicz, R.R. Negenborn, Z. Papp, D. Djairam, B. De Schutter, J. J. Smit. Optimization of condition-based asset management using a predictive health model. In Proceedings of the 16th International Symposium on High Voltage Engineering (ISH 2009), Cape Town, South Africa, August 2009.Electrical Sustainable EnergyElectrical Engineering, Mathematics and Computer Scienc
Het ontwerp van intelligente software voor energiebezuiniging met behulp van patroonherkenning in het elektriciteitsverbruik
No full textThis thesis presents software that controls electrical household appliances. It uses an intelligent algorithm that adapts to the use of these household appliances by recognizing patterns of electricity useage.Electrical Engineering, Mathematics and Computer Scienc
Challenges for process system engineering in infrastructure operation and control
No full textThe need for improving the operation and control of infrastructure systems has created a demand on optimization methods applicable in the area of complex sociotechnical systems operated by a multitude of actors in a setting of decentralized decision making. This paper briefly presents main classes of optimization models applied in PSE system operation, explores their applicability in infrastructure system operation and stresses the importance of multi-level optimization and multi-agent model predictive control. If you want to cite this report, please use the following reference instead: Z. Lukszo, M.P.C. Weijnen, R.R. Negenborn, B. De Schutter, and M. Ilic, “Challenges for process system engineering in infrastructure operation and control,” in 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering (Garmisch-Partenkirchen, Germany, July 2006) (W. Marquardt and C. Pantelides, eds.), vol. 21 of Computer-Aided Chemical Engineering, Amsterdam, The Netherlands: Elsevier, ISBN 978-0-444-52969-5, pp. 95–100, 2006.Delft Center for Systems and ControlMechanical, Maritime and Materials Engineerin
Adaptive control for autonomous ships with uncertain model and unknown propeller dynamics
No full textMotion control is one of the most critical aspects in the design of autonomous ships. During maneuvering, the dynamics of propellers as well as the craft hydrodynamical specifications experience severe uncertainties. In this paper, an adaptive control approach is proposed to control the motion and trajectory tracking of an autonomous vessel by adopting neural networks that is used for estimating the dynamics of the propellers and handling hydrodynamical uncertainties. Considering that the maneuvering model of a vessel resemble a nonlinear non-affine-in-control system, the proposed neural-based adaptive control algorithm is designed to estimate the nonlinear influence of the input function which in this case is the dynamics of propellers and thrusters. It is also shown that the proposed methodology is capable of handling state dependent uncertainties within the ship maneuvering model. A Lyapunov-based technique and Uniform Ultimate Boundedness are used to prove the correctness of the algorithm. To assess the method's performance, several experiments are considered including trajectory tracking simulations in the port of Rotterdam.Accepted Author ManuscriptTransport Engineering and Logistic
Control and Coordination for Automated Container Terminals
No full textFor enhancing the performance of automated container terminals, this PhD thesis focuses on improving energy efficiency and implementing more autonomous equipment (e.g., free-ranging AGVs) at the operational level. On the one hand, due to the increased energy price and environmental stress, energy efficiency needs to be improved. On the other hand, new emerging AGVs allow free-ranging behavior and can shorten the driving distance than using the traditional routing strategy, demanding a novel advanced control algorithm for scheduling and controlling the free-ranging AGVs and the other related machines. For achieving these research goals, both discrete-event dynamics and continuous-time dynamics are considered in this thesis, using a perspective of hybrid systems. Simulation experiments on compact, medium and large-scale terminal case studies show the potential of the proposed new approaches.Maritime and Transportation TechnologyMechanical, Maritime and Materials Engineerin
Predictive mechanical model for fracture stimulation in an enhanced geothermal system (EGS) context
No full textAccepted Author ManuscriptReservoir EngineeringApplied Geolog
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