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Relevant bibliographies by topics / Real-Time Dynamic Programming

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Academic literature on the topic 'Real-Time Dynamic Programming'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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Journal articles on the topic "Real-Time Dynamic Programming"

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Gehani, Narain, and Krithi Ramamritham. "Real-time Concurrent C: A language for programming dynamic real-time systems." Real-Time Systems 3, no. 4 (1991): 377–405. http://dx.doi.org/10.1007/bf00365999.

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Li, Guoliang, Mohammad N. A. Rana, Jinhong Sun, Yinglei Song, and Junfeng Qu. "Real-time image enhancement with efficient dynamic programming." Multimedia Tools and Applications 79, no. 41-42 (2020): 30883–903. http://dx.doi.org/10.1007/s11042-020-09586-y.

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Barto, Andrew G., Steven J. Bradtke, and Satinder P. Singh. "Learning to act using real-time dynamic programming." Artificial Intelligence 72, no. 1-2 (1995): 81–138. http://dx.doi.org/10.1016/0004-3702(94)00011-o.

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Tew, A. I., and C. J. Gray. "A real-time gesture recognizer based on dynamic programming." Journal of Biomedical Engineering 15, no. 3 (1993): 181–87. http://dx.doi.org/10.1016/0141-5425(93)90113-d.

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Cui, Xi Min, Ke Zheng, Chang Ru Liu, and Qiong Zheng. "Multi-Threaded Technology Apply in Real Time Measurement System of Dual-Camera." Applied Mechanics and Materials 687-691 (November 2014): 966–69. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.966.

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Based on multi-thread technology, completed a set of real-time dynamic measurement system apply on binocular vision principle. Real time measurement require of system efficiency higher, multithreaded programming can greatly improve the efficiency of program. Binocular dynamic real-time detection is based on closed-loop control system, puts forward a multithreaded programming technology which is based on the binocular vision high-speed dynamic measurement method. The data acquisition, processing, display are using multithreading technology.

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Mouawad, Grace, Maroun Nemer, and Khalil El Khoury. "Real Time Dynamic Programming Control of Rapid Thermal Processing Furnaces." Numerical Heat Transfer, Part A: Applications 64, no. 11 (2013): 920–37. http://dx.doi.org/10.1080/10407782.2013.807694.

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Gong, Minglun, and Yee-Hong Yang. "Real-Time Stereo Matching Using Orthogonal Reliability-Based Dynamic Programming." IEEE Transactions on Image Processing 16, no. 3 (2007): 879–84. http://dx.doi.org/10.1109/tip.2006.891344.

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Matthews, B., and I. Elhanany. "Hardware architecture for high-speed real-time dynamic programming applications." IET Computers & Digital Techniques 2, no. 3 (2008): 164. http://dx.doi.org/10.1049/iet-cdt:20070027.

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FAN, Chang-Jie, and Xiao-Ping CHEN. "Optimal Action Criterion and Algorithm Improvement of Real-Time Dynamic Programming." Journal of Software 19, no. 11 (2009): 2869–78. http://dx.doi.org/10.3724/sp.j.1001.2008.02869.

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Korotkova, Yu L., and Yu A. Mezentsev. "The dynamic programming algorithm for management of real-time aircraft assignments." Journal of Physics: Conference Series 1333 (October 2019): 032040. http://dx.doi.org/10.1088/1742-6596/1333/3/032040.

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Dissertations / Theses on the topic "Real-Time Dynamic Programming"

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Zhou, Yongjun. "Execution time analysis for dynamic real-time systems." Ohio : Ohio University, 2002. http://www.ohiolink.edu/etd/view.cgi?ohiou1175011592.

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Thompson, Dean (Dean Barrie) 1974. "Dynamic reconfiguration under real-time constraints." Monash University, School of Computer Science and Software Engineering, 2002. http://arrow.monash.edu.au/hdl/1959.1/7991.

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Singels, Francois. "Real-time stereo reconstruction using hierarchical dynamic programming and LULU filtering." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4294.

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Thesis (MSc (Mathematics))--University of Stellenbosch, 2010.<br>ENGLISH ABSTRACT: In this thesis we consider the essential topics relating to stereo-vision and the correspondence problem in general. The aim is to reconstruct a dense 3D scene from images captured by two spatially related cameras. Our main focus, however, is on speed and real-time implementation on a standard desktop PC. We wish to use the CPU to solve the correspondence problem and to reserve the GPU for model rendering. We discuss three fundamental types of algorithms and evaluate their suitability to this end. We eventually choose to implement a hierarchical version of the dynamic programming algorithm, because of the good balance between accuracy and speed. As we build our system from the ground up we gradually introduce necessary concepts and established geometric principles, common to most stereovision systems, and discuss them as they become relevant. It becomes clear that the greatest weakness of the hierarchical dynamic programming algorithm is scanline inconsistency. We nd that the one-dimensional LULU- lter is computationally inexpensive and e ective at removing outliers when applied across the scanlines. We take advantage of the hierarchical structure of our algorithm and sub-pixel re nement to produce results at video rates (roughly 20 frames per second). A 3D model is also constructed at video rates in an on-line system with only a small delay between obtaining the input images and rendering the model. Not only is the quality of our results highly competitive with those of other state of the art algorithms, but the achievable speed is also considerably faster.<br>AFRIKAANSE OPSOMMING: In hierdie tesis beskou ons die noodsaaklike onderwerpe wat in die algemeen verband hou met stereovisie en die ooreenstemmingsprobleem. Die mikpunt is om 'n digte 3D toneel te rekonstrueer vanaf beelde wat deur twee ruimtelik-verwante kameras vasgelê is. Ons hoofdoel is egter spoed, en intydse implementering op 'n standaard rekenaar. Ons wil die SVE (CPU) gebruik om die ooreenstemmingsprobleem op te los, en reserveer die GVE (GPU) vir model-beraping. Ons bespreek drie fundamentele tipes algoritmes en evalueer hul geskiktheid vir hierdie doel. Ons kies uiteindelik om 'n hiërargiese weergawe van die dinamiese programmeringsalgoritme te implementeer, as gevolg van die goeie balans tussen akkuraatheid en spoed. Soos wat ons ons stelsel van die grond af opbou, stel ons geleidelik nodige konsepte voor en vestig meetkundige beginsels, algemeen tot meeste stereovisie stelsels, en bespreek dit soos dit toepaslik word. Dit word duidelik dat skandeerlyn-strydigheid die grootste swakheid van die hiërargiese dinamiese programmeringsalgoritme is. Ons vind dat die een-dimensionele LULU- lter goedkoop is in terme van berekeninge, en e ektief aangewend kan word om uitskieters te verwyder as dit dwarsoor skandeerlyne toegepas word. Ons buit die hiërargiese struktuur van ons algoritme uit en kombineer dit met sub-piksel verfyning om resultate te produseer teen video tempo (ongeveer 20 raampies per sekonde). 'n 3D model word ook gekonstrueer teen video tempo in 'n stelsel wat aanlyn loop, met slegs 'n klein vertraging tussen die verkryging van die intree-beelde en die beraping van die model. Die kwaliteit van ons resultate is nie net hoogs mededingend met dié van die heel beste algoritmes nie, maar die verkrygbare spoed is ook beduidend vinniger.

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Huh, Eui-Nam. "Certification of real-time performance for dynamic, distributed real-time systems." Ohio : Ohio University, 2002. http://www.ohiolink.edu/etd/view.cgi?ohiou1178732244.

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Tosukhowong, Thidarat. "Dynamic Real-time Optimization and Control of an Integrated Plant." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14087.

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Applications of the existing steady-state plant-wide optimization and the single-scale fast-rate dynamic optimization strategies to an integrated plant with material recycle have been impeded by several factors. While the steady-state optimization formulation is very simple, the very long transient dynamics of an integrated plant have limited the optimizers execution rate to be extremely low, yielding a suboptimal performance. In contrast, performing dynamic plant-wide optimization at the same rate as local controllers requires exorbitant on-line computational load and may increase the sensitivity to high-frequency dynamics that are irrelevant to the plant-level interactions, which are slow-scale in nature. This thesis proposes a novel multi-scale dynamic optimization and control strategy suitable for an integrated plant. The dynamic plant-wide optimizer in this framework executes at a slow rate to track the slow-scale plant-wide interactions and economics, while leaving the local controllers to handle fast changes related to the local units. Moreover, this slow execution rate demands less computational and modeling requirement than the fast-rate optimizer. An important issue of this method is obtaining a suitable dynamic model when first-principles are unavailable. The difficulties in the system identification process are designing proper input signal to excite this ill-conditioned system and handling the lack of slow-scale dynamic data when the plant experiment cannot be conducted for a long time compared to the settling time. This work presents a grey-box modeling method to incorporate steady-state information to improve the model prediction accuracy. A case study of an integrated plant example is presented to address limitations of the nonlinear model predictive control (NMPC) in terms of the on-line computation and its inability to handle stochastic uncertainties. Then, the approximate dynamic programming (ADP) framework is investigated. This method computes an optimal operating policy under uncertainties off-line. Then, the on-line multi-stage optimization can be transformed into a single-stage problem, thus reducing the real-time computational effort drastically. However, the existing ADP framework is not suitable for an integrated plant with high dimensional state and action space. In this study, we combine several techniques with ADP to apply nonlinear optimal control to the integrated plant example and show its efficacy over NMPC.

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Marrison, N. A. "Real time fault detection and diagnosis in dynamic engineering systems using constraint analysis." Thesis, University of Glasgow, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309807.

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Forbes, Harold C. "Operating system principles and constructs for dynamic multi-processor real-time control systems." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/8165.

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Ramachandran, Adithya. "HEV fuel optimization using interval back propagation based dynamic programming." Thesis, Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/55054.

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In this thesis, the primary powertrain components of a power split hybrid electric vehicle are modeled. In particular, the dynamic model of the energy storage element (i.e., traction battery) is exactly linearized through an input transformation method to take advantage of the proposed optimal control algorithm. A lipschitz continuous and nondecreasing cost function is formulated in order to minimize the net amount of consumed fuel. The globally optimal solution is obtained using a dynamic programming routine that produces the optimal input based on the current state of charge and the future power demand. It is shown that the global optimal control solution can be expressed in closed form for a time invariant and convex incremental cost function utilizing the interval back propagation approach. The global optimality of both time varying and invariant solutions are rigorously proved. The optimal closed form solution is further shown to be applicable to the time varying case provided that the time variations of the incremental cost function are sufficiently small. The real time implementation of this algorithm in Simulink is discussed and a 32.84 % improvement in fuel economy is observed compared to existing rule based methods.

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Luscombe, Ruth. "A dynamic real time scheduling methodology for the emergency department." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/86505/1/Ruth_Luscombe_Thesis.pdf.

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This project constructs a scheduling solution for the Emergency Department. The schedules are generated in real-time to adapt to new patient arrivals and changing conditions. An integrated scheduling formulation assigns patients to beds and treatment tasks to resources. The schedule efficiency is assessed using waiting time and total care time experienced by patients. The solution algorithm incorporates dispatch rules, meta-heuristics and a new extended disjunctive graph formulation which provide high quality solutions in a fast time-frame for real time decision support. This algorithm can be implemented in an electronic patient management system to improve patient flow in the Emergency Department.

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Haerian, Laila. "Airline Revenue Management: models for capacity control of a single leg and a network of flights." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1181839192.

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Books on the topic "Real-Time Dynamic Programming"

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author, Ranapariya Vishal, ed. Java Hibernate cookbook: Over 50 recipes to help you build dynamic and powerful real-time Java Hibernate applications. Packt Publishing, 2015.

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Hayes-Roth, Barbara. An architecture for adaptive intelligent systems. Stanford University, Dept. of Computer Science, 1993.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., ed. Real-Time Multiprocessor Programming Language (RTMPL): Users manual. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., ed. Real-Time Multiprocessor Programming Language (RTMPL): Users manual. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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A, Caglayan, and Dryden Flight Research Facility, eds. Expert systems for real-time monitoring and fault diagnosis. National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1989.

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Real-Time Multiprocessor Programming Language (RTMPL): Users manual. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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Expert systems for real-time monitoring and fault diagnosis. National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1989.

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Back, Kerry E. Real Options and q Theory. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190241148.003.0020.

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The theory of perpetual options and dynamic programming are applied to analyze the optimal capital investment of a firm. When investment is continuous and capital is the numeraire, the marginal value of capital is called marginal q. The optimal investment rate is a function of marginal q. When investment is irreversible and there is no depreciation, the optimal time to make each marginal investment is given by the theory of perpetual options. The optimal invesment times can also be calculated by dynamic programming. Fluctuations in marginal q add risk to a firm, compared to reversible investment. The Berk‐Green‐Naik model is an example of a model that relates risk and expected return to size and book‐to‐market by endogenizing investment.

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Algebraic Statistics. American Mathematical Society, 2018.

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Book chapters on the topic "Real-Time Dynamic Programming"

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Kohn, Wolf, and Jeffrey B. Remmel. "Hybrid dynamic programming." In Hybrid and Real-Time Systems. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0014740.

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Buhmann, M. D., Prem Melville, Vikas Sindhwani, et al. "Real-Time Dynamic Programming." In Encyclopedia of Machine Learning. Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_701.

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Kakas, Antonis C., David Cohn, Sanjoy Dasgupta, et al. "Adaptive Real-Time Dynamic Programming." In Encyclopedia of Machine Learning. Springer US, 2011. http://dx.doi.org/10.1007/978-0-387-30164-8_10.

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Barto, Andrew G. "Adaptive Real-Time Dynamic Programming." In Encyclopedia of Machine Learning and Data Mining. Springer US, 2017. http://dx.doi.org/10.1007/978-1-4899-7687-1_10.

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Delgado, Karina Valdivia, Cheng Fang, Scott Sanner, and Leliane Nunes de Barros. "Symbolic Bounded Real-Time Dynamic Programming." In Advances in Artificial Intelligence – SBIA 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16138-4_20.

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Salmen, Jan, Marc Schlipsing, Johann Edelbrunner, Stefan Hegemann, and Stefan Lüke. "Real-Time Stereo Vision: Making More Out of Dynamic Programming." In Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03767-2_133.

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Kim, Yong, and Hong Jeong. "Two-Level Dynamic Programming Hardware Implementation for Real Time Processing." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11892960_131.

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Pratikakis, Nikolaos E., Matthew J. Realff, and Jay H. Lee. "A Real Time Approximate Dynamic Programming Approach: A High Dimensional Supply Chain Application." In Process Systems Engineering. Wiley-VCH Verlag GmbH & Co. KGaA, 2014. http://dx.doi.org/10.1002/9783527631209.ch34.

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Pratikakis, Nikolaos E., Matthew J. Realff, and Jay H. Lee. "A Real Time Approximate Dynamic Programming Approach: A High Dimensional Supply Chain Application." In Process Systems Engineering. Wiley-VCH Verlag GmbH & Co. KGaA, 2011. http://dx.doi.org/10.1002/9783527631278.ch3.

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Walrand, Jean. "Route Planning: A." In Probability in Electrical Engineering and Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-49995-2_13.

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AbstractThis chapter is concerned with making successive decisions in the presence of uncertainty. The decisions affect the cost at each step but also the “state” of the system. We start with a simple example: choosing a route with uncertain travel times. We then examine a more general model: controlling a Markov chain.Section 13.1 presents a model of route section when the travel times are random. Section 13.2 shows one formulation where one plans the trip long in advance. Section 13.3 explains how the problem changes if one is able to adjust the route based on real-time information. That section introduces the main ideas of stochastic dynamic programming. Section 13.4 discusses a generalization of the route planning problem: a Markov decision problem. Section 13.5 solves the problem when the horizon is infinite.

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Conference papers on the topic "Real-Time Dynamic Programming"

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McMahan, H. Brendan, Maxim Likhachev, and Geoffrey J. Gordon. "Bounded real-time dynamic programming." In the 22nd international conference. ACM Press, 2005. http://dx.doi.org/10.1145/1102351.1102423.

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Fan, Changjie, and Xiaoping Chen. "Bounded Incremental Real-Time Dynamic Programming." In 2007 Frontiers in the Convergence of Bioscience and Information Technologies. IEEE, 2007. http://dx.doi.org/10.1109/fbit.2007.14.

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Schmoll, Sebastian, and Matthias Schubert. "Dynamic Resource Routing using Real-Time Dynamic Programming." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/670.

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Acquiring available resources in stochastic environments becomes more and more important to future mobility. For instance, cities like Melbourne, Canberra and San Francisco install sensors that detect in real-time whether a parking spot (resource) is available or not. In such environments, the current state of the resources may be fully observable, although the future development is stochastic. In order to reduce the traffic, such cities want to fully exploit parking spots, such that the amount of searching cars is minimized. Thus, we formulate a problem setting where the expected seek time for each driver is minimized. This problem can be modeled by a Markov Decision Process (MDP) and solved using standard algorithms. In this paper, we focus on the setting, where pre-computation is not possible and search policies have to be computed on the fly. Our approach is based on state-of-the-art Real-Time Dynamic Programming (RTDP) approaches. However, standard RTDP approaches do not perform well on this specific problem setting as shown in our experiments. We introduce adapted bounds and approximations that exploit the specific nature of the problem in order to improve the performance significantly.

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Kong, Kyoungchul, Kiyonori Inaba, and Masayoshi Tomizuka. "Real-Time Nonlinear Programming by Amplitude Modulation." In ASME 2008 Dynamic Systems and Control Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/dscc2008-2160.

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Nonlinear Programming (NLP) is for optimization of nonlinear cost functions. In applications of NLP for real-time optimization, however, the estimation of the gradient of the cost function remains as a challenge. On the other hand, the Extremum-Seeking Control (ESC) optimizes the cost function in real-time, but it involves a complicated design of filters in multi-dimensional cases. In this paper, a new method that optimizes an arbitrary multi-variable cost function in real-time is proposed. In the proposed method, the variables are updated as in NLP while the gradient of the cost function is continuously estimated by the amplitude modulation as in ESC. The proposed method does not require design of any complicated filters. The performance is verified by simulations on time-varying and noisy cost functions as well as automatic controller tuning applications.

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Matthews, Brad, and Itamar Elhanany. "Scalable Hardware Architecture for Real-Time Dynamic Programming Applications." In 2006 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines. IEEE, 2006. http://dx.doi.org/10.1109/fccm.2006.61.

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Ma, Zhiqiang, Zhengxiong Liu, and Chengxu Ge. "Deploying Strategy of Tethered Space Robot with Approximate Dynamic Programming." In 2020 IEEE International Conference on Real-time Computing and Robotics (RCAR). IEEE, 2020. http://dx.doi.org/10.1109/rcar49640.2020.9303326.

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HuH, Dongsung, and Emanuel Todorov. "Real-time motor control using recurrent neural networks." In 2009 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL). IEEE, 2009. http://dx.doi.org/10.1109/adprl.2009.4927524.

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Plamondon, Pierrick, Brahim Chaib-draa, and Abder Rezak Benaskeur. "A Real-time Dynamic Programming Decomposition Approach to Resource Allocation." In 2007 Information, Decision and Control. IEEE, 2007. http://dx.doi.org/10.1109/idc.2007.374568.

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Mohd Zulkefli, Mohd Azrin, and Zongxuan Sun. "Real-Time Powertrain Optimization Strategy for Connected Hybrid Electrical Vehicle." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9727.

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Connected Vehicle (CV) technology, which allows traffic information sharing, and Hybrid Electrical Vehicles (HEV) can be combined to improve vehicle fuel efficiency. However, transient traffic information in CV environment necessitates a fast HEV powertrain optimization for real-time implementation. Model Predictive Control (MPC) with Linearization is proposed, but the computational effort is still prohibitive. The Equivalent Consumption Minimization Strategy (ECMS) and Adaptive-ECMS are proposed to minimize computation time, but unable to guarantee charge-sustaining-operation (CS). Fast analytical result from Pontryagin’s Minimum Principles (PMP) is possible but the input has to be unconstrained. Numerical solutions with Linear Programming (LP) are proposed, but over-simplifications of the cost and constraint functions limit the performance of such methods. In this paper, a nonlinear CS constraint is transformed into linear form with input variable change. With linear input and CS constraints, the problem is solved with Separable Programming by approximating the nonlinear cost with accurate linear piecewise functions which are convex. The piecewise-linear functions introduce new dimensionless variables which are solved as a large-dimension constrained linear problem with efficient LP solvers. Comparable fuel economy with Dynamic Programming (DP) is shown, with maximum fuel savings of 7% and 21.4% over PMP and Rule-Based (RB) optimizations. Simulations with different levels of vehicle speed prediction uncertainties to emulate CV settings are presented.

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Boedecker, Joschka, Jost Tobias Springenberg, Jan Wulfing, and Martin Riedmiller. "Approximate real-time optimal control based on sparse Gaussian process models." In 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL). IEEE, 2014. http://dx.doi.org/10.1109/adprl.2014.7010608.

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Reports on the topic "Real-Time Dynamic Programming"

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Morkun, Vladimir S., Natalia V. Morkun, and Andrey V. Pikilnyak. Augmented reality as a tool for visualization of ultrasound propagation in heterogeneous media based on the k-space method. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3757.

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For programming the AR tools, interactive objects and creating the markers, the method of fiber spaces (k-space) for modeling of ultrasonic wave propagation in an inhomogeneous medium using coarse grids, with maintaining the required accuracy was used. The algorithm and tools of augmented reality were introduced into the adaptive control system of the pulp gas phase in the iron ore flotation process using a control action on the basis of high-energy ultrasound dynamic effects generated by ultrasonic phased arrays. The tools of augmented reality based on k-space methods allow to facilitate wider adoption of ultrasound technology and visualize the ultra-sound propagation in heterogeneous media by providing a specific correspondence between the ultrasound data acquired in real- time and a sufficiently detailed augmented 3D scene. The tools of augmented reality allow seeing the field of ultrasound propagation, its characteristics, as well as the effect of the dynamic effects of ultrasound on the change in the gas phase during the flotation process.

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