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Batch size effects on the efficiency of control variates in simulation

Barry L. Nelson
1989 European Journal of Operational Research  
This paper considers the combined use of control variates and batching for estimating the steady-state mean of an infinite-horizon process via simulation.  ...  Properties of the point and interval estimators from such a procedure are derived as functions of the number of batches and the number of control variates when the total sample size is fixed.  ...  Neuhardt of The Ohio State University, Bruce Schmeiser, and James R. Wilson of Purdue University, and comments by two anonymous referees, one of whom suggested the alternate expression for Result 3.  ... 
doi:10.1016/0377-2217(89)90212-9 fatcat:wwtb7rh6trfpra5rq4nnqyvqcu

Optimization via simulation: A review

Michael C. Fu
1994 Annals of Operations Research  
We review techniques for optimizing stochastic discrete-event systems via simulation.  ...  In practice, the pooled variance could be used to estimate the additional number of replications needed to make a final determination. where J i and s have the same meaning as in the MCA procedure.  ...  In particular, the independence assumption would rule out the implementation of powerful variance reduction techniques such as common random numbers and control variates.  ... 
doi:10.1007/bf02136830 fatcat:srcum3kqvzh33gbd4g3kghncje

Lidar-assisted model predictive control of wind turbine fatigue via online rainflow counting considering stress history

Stefan Loew, Carlo L. Bottasso
2022 Wind Energy Science  
The formulation is tested in realistic simulation scenarios in which the states are estimated by a moving horizon estimator and the wind is predicted by a lidar simulator.  ...  The tuning procedure for the controller toolchain is carefully explained.  ...  The authors would like to thank the company sowento GmbH for kindly providing a free license of their lidar simulator.  ... 
doi:10.5194/wes-7-1605-2022 fatcat:h5azjwl74fhhrahq6xio5m4s5a

Automated Verification and Synthesis of Stochastic Hybrid Systems: A Survey [article]

Abolfazl Lavaei, Sadegh Soudjani, Alessandro Abate, Majid Zamani
2022 arXiv   pre-print
Automated verification and policy synthesis for stochastic hybrid systems can be inherently challenging: this is due to the heterogeneity of their dynamics (presence of continuous and discrete components  ...  In this survey, we overview the most recent results in the literature and discuss different approaches, including (in)finite abstractions, verification and synthesis for temporal logic specifications,  ...  We hope that this survey article provides an introduction to the foundations of SHS, towards an easier understanding of many challenges and existing solutions related to formal verification and control  ... 
arXiv:2101.07491v2 fatcat:dpir554ebfclhpj5m7e7fi2hv4

A Deep Reinforcement Learning Framework for Eco-driving in Connected and Automated Hybrid Electric Vehicles [article]

Zhaoxuan Zhu, Shobhit Gupta, Abhishek Gupta, Marcello Canova
2021 arXiv   pre-print
An Eco-driving simulation environment is developed for training and evaluation purposes.  ...  Connected and Automated Vehicles (CAVs), in particular those with multiple power sources, have the potential to significantly reduce fuel consumption and travel time in real-world driving conditions.  ...  ACKNOWLEDGMENT The authors acknowledge the support from the United States Department of Energy, Advanced Research Projects Agency -Energy (ARPA-E) NEXTCAR project (Award Number DE-AR0000794) and The Ohio  ... 
arXiv:2101.05372v2 fatcat:euqqbueed5fmpbubqal64tokqa

Deep Bayesian inference for seismic imaging with tasks [article]

Ali Siahkoohi and Gabrio Rizzuti and Felix J. Herrmann
2022 arXiv   pre-print
For instance, it admits estimates for the pointwise standard deviation on the image and for confidence intervals on its automatically tracked horizons.  ...  to uncertainty on the tracked horizons.  ...  [53] showed that for infinitely wide CNNs, i.e.  ... 
arXiv:2110.04825v3 fatcat:bqwegxozabcxxm7r4mfnrbxpxu

A real-time and eco-layout platform for optimization of supply/costs for water distribution systems management

Sabrine Atashin, Mohammad Hossein Niksokhan, Mohammad Ali Zahed
2022 Water Science and Technology : Water Supply  
Operating view is provided through a real-time control scheduler (RTC), which satisfactorily attends to solve the dynamic control problem at every timestep via minimization of energy costs over the day  ...  and satisfying hydraulic reliability constraints through suggesting near-optimal pump schedules.  ...  For any pump, the daily energy cost referred to the cost for each selected timestep (k) within the control horizon (T). Therefore, the cost for each pump (J p ) achieves via Equation (1).  ... 
doi:10.2166/ws.2022.258 fatcat:t326gs3kr5berkakkqvnyvz4lm

Stochastic process in railway traffic flow: Models, methods and implications

Francesco Corman, Alessio Trivella, Mehdi Keyvan-Ekbatani
2021 Transportation Research Part C: Emerging Technologies  
One potential for automation is the reduction of those margins by means of optimized traffic management and train control, for an estimated increase of 30% in the transport capacity.  ...  The models can be useful to estimate the benefits introduced by automation in railways, including Automated Train Operation (ATO). 2 aspects (see Wang et al., 2020b for frequency-domain stability analysis  ...  Zhou et al. (2017) developed a rolling horizon stochastic optimal control framework for Adaptive Cruise Control and Cooperative Adaptive Cruise Control.  ... 
doi:10.1016/j.trc.2021.103167 fatcat:nr6b6dsjynefpbipuypw4tkqj4

Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision

Bastien Berret, Adrien Conessa, Nicolas Schweighofer, Etienne Burdet, Ulrik R. Beierholm
2021 PLoS Computational Biology  
errors based on the available limb state estimate.  ...  In SFFC, movement timing results from the minimization of the intrinsic factors of effort and variance due to constant and signal-dependent motor noise, and movement variability depends on the integration  ...  For instance, [22] determined duration in an infinite-horizon SOC formulation by comparing the magnitude of endpoint variance to the target's width, which allowed to predict the speed-accuracy trade-off  ... 
doi:10.1371/journal.pcbi.1009047 pmid:34115757 fatcat:6fvsk4nv7facncu2tbdadlq7i4

Stochastic optimal feedforward-feedback control determines timing and variability of arm movements with or without vision

Etienne Burdet
2021 figshare.com  
errors based on the available limb state estimate.  ...  In SFFC, movement timing results from the minimization of the intrinsic factors of effort and variance due to constant and signal-dependent motor noise, and movement variability depends on the integration  ...  For instance, [22] determined duration in an infinite-horizon SOC formulation by comparing the magnitude of endpoint variance to the target's width, which allowed to predict the speed-accuracy trade-off  ... 
doi:10.6084/m9.figshare.16567626.v1 fatcat:btzxhc7c6ndzjo3x54eoger4uq

Frenet-Based Algorithm for Trajectory Prediction

Giulio Avanzini
2004 Journal of Guidance Control and Dynamics  
Unfortunately no such a priori estimate is possible for the process noise variance a, or, equivalently, for the ratio a, /o,.  ...  In this case, the white noise variance is 0, = 0.1 deg-s ! and also in this case, the error rms for the estimated signal is less then 4 g,.  ... 
doi:10.2514/1.9338 fatcat:j5sfv4x3ozh5totvvl53hfa3au

A New Efficient Adaptive Control of Torsional Vibrations Induced by Switched Nonlinear Disturbances

Maciej Wasilewski, Dominik Pisarski, Robert Konowrocki, Czesław I. Bajer
2019 International Journal of Applied Mathematics and Computer Science  
The controller's performance is examined via numerical simulations of the stabilization of the drilling system.  ...  This approach allows generating a control law that takes into account the impact of the friction on the system dynamics and optimally steers the system to the desired trajectory.  ...  for the result of simulation governed with noise variance g = 200 N 2 m 2 and J1 stands for the trajectory of simulation with the noise variance g = 1 N 2 m 2 ) (a), control values generated by Algorithm  ... 
doi:10.2478/amcs-2019-0021 fatcat:6tibm4bczvgifb2cldfevklk5i

The role of statistical methodology in simulation

Jack P. C. Kleijnen
1978 ACM SIGSIM Simulation Digest  
For Monte Carlo simulations some tactical problems are discussed: runlength and variance reduction.  ...  In stochastic simulation two tactical problems exist: Variance reduction can be achieved through special techniques such as common random numbers, antithetic variates, control variates (regression sampling  ...  If we wish to estimate, say, average waiting time n for a specific average input value y, then we may correct our estimate via the regression model yi -BO t S1 . xi t ui (i-1,...  ... 
doi:10.1145/1102786.1102793 fatcat:pgyvsk3wxzdw7n5aaxcgvjmdpu

2020 Index IEEE Transactions on Automation Science and Engineering Vol. 17

2020 IEEE Transactions on Automation Science and Engineering  
., +, TASE July 2020 1237-1249 Infinite horizon Supervisory Model Predictive Control for Optimal Energy Management of Networked Smart Greenhouses Integrated Microgrid.  ...  Yan, J., +, TASE July 2020 1361-1375 Variation Source Identification in Manufacturing Processes Using Bayesian Approach With Sparse Variance Components Prior.  ...  Project management Solving the Tree-Structured Task Allocation Problem via Group Multirole Assignment.  ... 
doi:10.1109/tase.2020.3037603 fatcat:kyt63444lfc45amrjebyjw34qu

Mitigating Bunching with Bus-following Models and Bus-to-Bus Cooperation

Konstantinos Ampountolas, Malcolm Kring
2015 2015 IEEE 18th International Conference on Intelligent Transportation Systems  
Then a combined state estimation and remote control scheme, which is based on the Linear-Quadratic Gaussian theory, is developed to capture the effect of bus stops, traffic disturbances, and randomness  ...  In this context, we first propose practical linear and nonlinear control laws to regulate space headways and speeds, which would lead to bunching cure.  ...  The infinite time horizon in (10) is taken in order to obtain a time-invariant feedback law according to the LQG control theory.  ... 
doi:10.1109/itsc.2015.18 dblp:conf/itsc/AmpountolasK15 fatcat:phh2mthmrndsfm7c6bund6ftgu
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