Готові списки джерел за темами / Simulation, modelling, and programming of mechatronics systems

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  1. Статті в журналах
  2. Дисертації
  3. Книги
  4. Частини книг
  5. Тези доповідей конференцій

Добірка наукової літератури з теми "Simulation, modelling, and programming of mechatronics systems"

Автор: Grafiati
Опубліковано: 20 грудня 2024

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Статті в журналах з теми "Simulation, modelling, and programming of mechatronics systems"

1

Malik, M. Afzaal, and Saheeb A. Kayani. "Verifying experiment for automated design of mechatronic systems using Bond-Graph modelling and simulation and genetic programming." International Journal of Computer Applications in Technology 32, no. 3 (2008): 173. http://dx.doi.org/10.1504/ijcat.2008.020952.

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2

Žemla, Filip, Ján Cigánek, Danica Rosinová, Erik Kučera, and Oto Haffner. "Complex Positioning System for the Control and Visualization of Photovoltaic Systems." Energies 16, no. 10 (2023): 4001. http://dx.doi.org/10.3390/en16104001.

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This paper presents a proposal of a complex mechatronic system that enhances the effectivity of obtaining energy from renewable resources. The main focus is on the photovoltaic energy system, which obtains electricity from the conversion of solar radiation through photovoltaic crystalline silicon-based panels. The design of the complex mechatronic system consists of several steps. The structural design of the photovoltaic panel positioning unit in the form of a three-dimensional model is made in the selected modelling programming environment. Subsequently, a propulsion system is proposed for t
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3

Gwiazda, A., W. Banaś, A. Sękala, G. Ćwikła, M. Sokół, and K. Foit. "Complex technical systems modelling and their mechatronics function simulation." IOP Conference Series: Materials Science and Engineering 400 (September 18, 2018): 042028. http://dx.doi.org/10.1088/1757-899x/400/4/042028.

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4

Sekala, A., G. Kost, W. Banas, A. Gwiazda, and C. Grabowik. "Modelling and simulation of robotic production systems." Journal of Physics: Conference Series 2198, no. 1 (2022): 012065. http://dx.doi.org/10.1088/1742-6596/2198/1/012065.

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Abstract Modern manufacturing systems consist of a sequence of robotic systems, such as robotic cells, which are widely used in the industry. As they become commonplace and play important roles in modern industrial production, efficient modelling and use of robotic cells become a necessity. Robotization brings many measurable benefits. It enables effective utilization of both human resources and the possessed machine park and thus contributing to the improvement of product quality and efficiency. Industrial robots not only increase the growth of productivity, by replacing man in monotonous wor
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5

Senthilnathan, K. "Development and Evaluation of Control System in Mechatronics – A Systematic Survey." Journal of Electrical Engineering and Automation 4, no. 2 (2022): 109–19. http://dx.doi.org/10.36548/jeea.2022.2.005.

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The advancement of mechatronic enabling technologies and the mechatronic design approach has resulted in sophisticated mechatronic systems. Automated mechatronic systems are becoming more complicated and more intelligent. Mechanical systems that enable the next generation of manufacturing systems will have whole new features and capabilities as a result of these modifications. Even basic monitoring has grown into self-optimizing performance in these gadgets. With the addition of bio-mechatronics and micro-mechatronics, the application fields of mechatronics have expanded. Bio or microcontrolle
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Verma, Deepak. "Modelling and Simulation of Mechatronic Systems for Predictive Performance Analysis." Mathematical Statistician and Engineering Applications 70, no. 1 (2021): 455–63. http://dx.doi.org/10.17762/msea.v70i1.2497.

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Modelling and simulation play a pivotal role in the development and analysis of mechatronic systems. The integration of mechanical, electrical, and control components in mechatronic systems creates complex dynamics that require comprehensive understanding and predictive performance analysis. This paper presents a thorough exploration of the use of modelling and simulation techniques for predictive performance analysis in mechatronic systems. This paper provides an in-depth examination of the role of modelling and simulation in the context of mechatronic systems for predictive performance analy
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7

Kim, Eungab, Mark P. Van Oyen, and Maria Rieders. "General dynamic programming algorithms applied to polling systems." Communications in Statistics. Stochastic Models 14, no. 5 (1998): 1197–221. http://dx.doi.org/10.1080/15326349808807520.

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8

Alzbutas, R., and V. Janilionis. "THE SIMULATION OF DYNAMIC SYSTEMS USING COMBINED MODELLING." Mathematical Modelling and Analysis 5, no. 1 (2000): 7–17. http://dx.doi.org/10.3846/13926292.2000.9637123.

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Анотація:
The new approach to the problems of dynamic systems simulation is proposed. The analytical and imitation modelling of non‐linear complex dynamic systems which comprise simulation of continuous and discrete processes with constant and variable parameters, are investigated. The aggregate mathematical modelling scheme [1] and the method of control sequences for discrete systems specification and simulation are used as well as the dynamic mathematical modelling scheme for continuous process formalization and modelling. According to them the investigated systems are presented as the set of interact
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9

Madhevan, B., R. Sakkaravarthi, G. Mandeep Singh, R. Diya, and Durgesh Kumar Jha. "Modelling, Simulation and Mechatronics Design of a Wireless Automatic Fire Fighting Surveillance Robot." Defence Science Journal 67, no. 5 (2017): 572. http://dx.doi.org/10.14429/dsj.67.10237.

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<span>The aim of this study is to design and develop an autonomous fire proof rescue robot. The robot is designed in such a way, that it can traverse through fire and hazardous situations. Further, it will sense and communicate information regarding these situations in real time with the server. The robot is fixed with multi-sensors and further, a driver circuit has been integrated for communication in these hazardous situations through Zigbee and a data acquisition system (DAQ). In mechanical design first, a 3D solid model is generated using Solid works software to understand the basic
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Soshko, Oksana. "Model-Based Supply Chain Management." Scientific Journal of Riga Technical University. Computer Sciences 45, no. 1 (2011): 116–22. http://dx.doi.org/10.2478/v10143-011-0052-z.

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Model-Based Supply Chain Management The paper is focused on application of modelling and simulation approaches in supply chain management. First, essentials of multi echelon supply chain management are discussed including the functionality of supply chain information systems. Then, a variety of modelling and simulation approaches are analyzed in the context of supply chain management, for example, simulation, stochastic programming, business process modelling and reference model. Finally, some illustrative examples are provided on application of simulation and modelling approaches to supply ch
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Дисертації з теми "Simulation, modelling, and programming of mechatronics systems"

1

Lavery, Eamonn. "Object oriented modelling and simulation of manufacturing systems." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361254.

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Di, Domenica Nico. "Stochastic programming and scenario generation : decision modelling simulation and information systems perspective." Thesis, Brunel University, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.415936.

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Gebremedhin, Mahder. "Automatic and Explicit Parallelization Approaches for Mathematical Simulation Models." Licentiate thesis, Linköpings universitet, Programvara och system, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117346.

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The move from single core and processor systems to multi-core and many-processors systemscomes with the requirement of implementing computations in a way that can utilizethese multiple units eciently. This task of writing ecient multi-threaded algorithmswill not be possible with out improving programming languages and compilers to providethe mechanisms to do so. Computer aided mathematical modeling and simulationis one of the most computationally intensive areas of computer science. Even simpli-ed models of physical systems can impose a considerable amount of computational loadon the processor
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4

Riederer, Peter. "Thermal room modelling adapted to the test of HVAC control systems." Doctoral thesis, [S.l. : s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=967121663.

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Riederer, Peter. "Thermal room modelling adapted to the test of HVAC control systems." Doctoral thesis, Technische Universität Dresden, 2001. https://tud.qucosa.de/id/qucosa%3A24191.

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Room models, currently used for controller tests, assume the room air to be perfectly mixed. A new room model is developed, assuming non-homogeneous room conditions and distinguishing between different sensor positions. From measurement in real test rooms and detailed CFD simulations, a list of convective phenomena is obtained that has to be considered in the development of a model for a room equipped with different HVAC systems. The zonal modelling approach that divides the room air into several sub-volumes is chosen, since it is able to represent the important convective phenomena imposed on
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6

Aoun, Nadine. "Modeling and flexible predictive control of buildings space-heating demand in district heating systems." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC104.

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La gestion de la demande en chauffage des bâtiments raccordés à des réseaux de chaleur s'effectue classiquement au moyen d’une courbe de chauffe : lorsque la température extérieure chute, la température de départ de l’eau alimentant le circuit de chauffage interne est relevée. Ce mode de contrôle, appelé régulation par loi d’eau, présente des atouts en termes de simplicité et de robustesse, mais ne tient pas compte de l'inertie thermique du bâtiment et ne permet donc pas une modulation de sa demande. La modulation de la demande en chauffage se définit comme l'action de contrôle consistant à mo
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Книги з теми "Simulation, modelling, and programming of mechatronics systems"

1

Damic, Vjekoslav. Mechatronics by bond graphs: An object-oriented approach to modelling and simulation. Springer, 2003.

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2

Pooch, Udo W. Discrete event simulation: A practical approach. CRC Press, 1993.

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3

Schetzen, Martin. Discrete systems laboratory using MATLAB. Brooks/Cole, 2000.

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4

Karnopp, Dean. System dynamics: A unified approach. 2nd ed. Wiley, 1990.

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5

Pelz, Georg. Mechatronic Systems: Modelling and Simulation with HDLs. Wiley & Sons, Incorporated, John, 2005.

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6

Montgomery, John, and Vjekoslav Damic. Mechatronics by Bond Graphs: An Object-Oriented Approach to Modelling and Simulation. Springer, 2016.

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7

Montgomery, John, and Vjekoslav Damic. Mechatronics by Bond Graphs: An Object-Oriented Approach to Modelling and Simulation. Springer London, Limited, 2016.

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Montgomery, John, and Vjekoslav Damic. Mechatronics by Bond Graphs: An Object-Oriented Approach to Modelling and Simulation. Springer, 2018.

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9

Artificial Intelligence, Expert Systems and Languages in Modelling and Simulation. Elsevier, 1988.

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10

(Editor), M. L. Brodie, J. Mylopoulos (Editor), and J. W. Schmidt (Editor), eds. On Conceptual Modelling: Perspectives from Artificial Intelligence, Databases, and Programming Languages (Topics in Information Systems). Springer, 1986.

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Частини книг з теми "Simulation, modelling, and programming of mechatronics systems"

1

Brezina, T., J. Vetiska, Z. Hadas, and L. Brezina. "Simulation Modelling and Control of Mechatronic Systems with Flexible Parts." In Mechatronics. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23244-2_69.

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2

Enge, Olaf, Gerald Kielau, and Peter Maißer. "Modelling and Simulation of Discrete Electromechanical Systems." In Proceedings of the Third Conference on Mechatronics and Robotics. Vieweg+Teubner Verlag, 1995. http://dx.doi.org/10.1007/978-3-322-91170-4_23.

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3

Granda, Jose J. "Automating the Process for Modeling and Simulation of Mechatronics Systems." In Bond Graph Modelling of Engineering Systems. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9368-7_11.

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4

Munteanu, Iulian Sorin, Liviu Marian Ungureanu, Cosmina-Constantina Caraiman, Ramona-Gabriela Crișan, Elisabeta Niculae, and Badea Sorin. "Modelling and Simulation of Some Mechatronics Assembly Realized on Arduino Uno Board, Through the Tinkercad Application." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-40628-7_31.

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5

Asgari, Hamid, XiaoQi Chen, and Raazesh Sainudiin. "Modelling and Simulation Approaches for Gas Turbine System Optimization." In Engineering Creative Design in Robotics and Mechatronics. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-4225-6.ch014.

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Анотація:
This chapter deals with research activities that have been carried out so far in the field of modelling and simulation of gas turbines for system optimization purposes. It covers major white-box and black-box gas turbine models and their applications to control systems.
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6

Nishad, Dinesh Kumar, A. N. Tiwari, and Saifullah Khalid. "Adaptive Control Algorithms for Shunt Active Power Filters in Aircraft Systems." In Advances in Mechatronics and Mechanical Engineering. IGI Global, 2024. https://doi.org/10.4018/979-8-3693-5797-2.ch004.

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Анотація:
Integrating power electronic converters and nonlinear loads in current aviation power systems has increased harmonic distortion, threatening power quality. Shunt active power filters (SAPFs) can reduce these harmonics by injecting compensatory currents to negate load harmonics. While simple, proportional-integral (PI) controllers have limits in transient response, steady-state performance, and resistance to dynamic load situations and system parameter fluctuations. Advanced adaptive control algorithms optimize performance in real time by dynamically adjusting parameters. This chapter discusses adaptive notch filters, self-tuning filters, fuzzy logic controllers, and dynamic programming controllers, including their principles, design, and implementation. These adaptive algorithms outperform standard harmonic mitigation and DC-link voltage regulation methods in simulation and experimentation. The findings suggest that adaptive control methods can improve SAPF efficiency and reliability in aircraft power systems, paving the door for hybrid and intelligent control research.
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7

GuarnierI, F., S. Olampi, and A. Napoli. "Toward a "Virtual Laboratory" to Support Forest Fire Behaviour Modelling and Metrology." In Environmental Information Systems in Industry and Public Administration. IGI Global, 2001. http://dx.doi.org/10.4018/978-1-930708-02-0.ch018.

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In forest fire research, it is now accepted that computational simulation and databases have become essential components of the scientific process, in order to combine theory and experiments. Although computers and software tools play a crucial role in the conduct of forest fire science today, scientists lack adequate software engineering tools to ease the construction, maintenance and reusability of modelling and database software. Usually, scientific models are implemented using a general-purpose programming language, such as Fortran C or C++. But since this type of general-purpose language is not specifically customised for scientific modelling problems, the scientist is forced to translate scientific constructs into general-purpose programming constructs in order to implement the model. This “manual’’ translation process can be very complicated, labor-intensive and error-prone. Furthermore, the translation process obfuscates the original scientific intent behind the model, and buries important assumptions in the program code that should remain explicit. The resulting code is often complex and difficult to understand for anyone but the original developers.
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Sulakhiya, Kunjbihari, Rishi Paliwal, Anglina Kisku, et al. "Experimental Tools as an “Alternative to Animal Research” in Pharmacology." In Software and Programming Tools in Pharmaceutical Research. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815223019124010010.

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Experimental tools have emerged as a promising alternative to animal research in pharmacology. With growing ethical concerns and regulatory restrictions surrounding animal experimentation, researchers are increasingly turning towards in vitro and in silico methods to develop new drugs and evaluate their safety and efficacy. In vitro tools include cell culture systems, 3D organoid models, and microfluidic devices replicating complex physiological conditions, such as the blood-brain barrier or the liver microenvironment. These systems can provide more accurate and predictive results than animal models, reducing ethical concerns and experimental costs. In silico methods, such as computer modelling, simulation, and artificial intelligence, enable researchers to predict the drug-target interactions, toxicity, and pharmacokinetic and pharmacodynamic properties of new drugs without animal testing. Experimental tools have several advantages over animal research, including more accurate and predictive results, lower costs, higher throughput, and reduced ethical concerns. However, the limitations of these tools must also be acknowledged, such as the inability to fully replicate the complexity of a living organism, which requires further validation. These tools offer a promising avenue for advancing pharmacological research while reducing the reliance on animal experimentation. In conclusion, experimental tools provide an excellent alternative to animal research in pharmacology to identify and avoid potential toxicities early in the drug discovery process and have the potential to revolutionize drug discovery and development. This chapter mainly focuses on the numerous in vitro, in silico, non-animal in vivo, and emerging experimental tools and their regulatory perspectives on validation, acceptance, and implementation of the alternative methods used in pharmacological research.
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Birtic, Martin, Pablo Morilla Cabello, Ángel Muñoz Rocha, and Anna Syberfeldt. "Exploring the Synergies of Modularization, Interface Standardization, and Service-Orientation in Production System Simulation." In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde240164.

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Production systems of the future may be in constant flux and reconfiguration, continuously adapting to changing production conditions. Digital models and simulation are powerful tools that can be used for their design and operation. These models must co-evolve with the physical system to sustain their usefulness and relevance. This poses a significant barrier, given the complexities involved in their efficient creation and maintenance. To understand whether certain system design concepts make the simulation process easier, this study aims to investigate a combination of concepts that promote reconfigurability and flexibility to explore whether they can positively influence the simulation process. By integrating modularization, interface standardization, and a service-oriented architecture it is believed to support faster and easier creation and updates of digital models. Modularization enhances flexibility by decomposing complex systems into independent, interchangeable modules. Standardizing interfaces ensures uniformity and compatibility among modules. Using a service-oriented architecture entails the encapsulation of various functionalities within modules as services, which can be dynamically requested. Shedding light on the advantages arising from modeling and simulating systems adhering to the mentioned concepts the research also aims to lay the groundwork for further investigation into the potential synergies of these promising production concepts. The study’s methodology includes modeling and programming of industrial robotic production modules adhering to predefined physical and logical interfaces. Interoperability and service orchestration are achieved through a service-oriented architecture. A simulated Manufacturing Execution System is integrated to facilitate handling of module services, product data and service requirements. Finally, a specialized software plugin was developed to support rapid module instantiation into a production system for evaluation. Results suggest that using a modular approach may ease modelling and simulation efforts and could be supported further by developing tailored tools for rapid system development.
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Тези доповідей конференцій з теми "Simulation, modelling, and programming of mechatronics systems"

1

Naebi, Ahmad, Farhad Khalegi, Farhood Hosseinpour, et al. "A New Flowchart and Programming Technique Using Bond Graph for Mechatronic Systems." In 2011 UkSim 13th International Conference on Computer Modelling and Simulation (UKSim). IEEE, 2011. http://dx.doi.org/10.1109/uksim.2011.52.

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Enikov, Eniko T., Qiuchen Zhang, and Lucas Creery. "System Identification and Controller Design of Propeller Driven Pendulum (Bi-Copter)." In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-109757.

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Abstract Undergraduate control courses are usually significantly improved when in-class instruction is backed up with experiments aimed at providing the students an opportunity of experiential learning. The rapid development of computer multimedia technology has resulted in a tendency toward a hands-on laboratory that incorporates simulation tools and computer-controlled equipment. However, most of the open-source hardware prototyping platforms require programming environments, installation of additional software, and additional plug-in modules that hinders the large-scale deployment of such s
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Peleteiro, Ana M., Juan C. Burguillo, Zuzana Oplatková, and Ivan Zelinka. "EPMAS: Evolutionary Programming Multi-Agent Systems." In 24th European Conference on Modelling and Simulation. ECMS, 2010. http://dx.doi.org/10.7148/2010-0027-0033.

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Abraham, Ajith, Crina Grosan, and Vaclav Snasel. "Programming Risk Assessment Models for Online Security Evaluation Systems." In 2009 11th International Conference on Computer Modelling and Simulation. IEEE, 2009. http://dx.doi.org/10.1109/uksim.2009.75.

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Senkerik, Roman, Zuzana Kominkova Oplatkova, Ivan Zelinka, and Michal Pluhacek. "Analytic Programming In The Task Of Evolutionary Synthesis Of The Robust Controller For Selected Discrete Chaotic Systems." In 27th Conference on Modelling and Simulation. ECMS, 2013. http://dx.doi.org/10.7148/2013-0398.

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Jurenoks, Vitalijs, Vladimirs Jansons, and Konstantins Didenko. "Modelling of Stability of Economic Systems Using Benchmarking and Dynamic Programming." In Tenth International Conference on Computer Modeling and Simulation (uksim 2008). IEEE, 2008. http://dx.doi.org/10.1109/uksim.2008.96.

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Grossschmidt, Gunnar, Mait Harf, and Taavi Sallaste. "Modelling and Simulation of Fluid Power Systems in Object-Oriented Programming Environment." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95387.

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The paper deals with principles of computer modelling and simulation of behaviour of fluid power systems in object-oriented programming environment. The approach is based on using multi-pole models and signal-flow graphs of functional elements, that enables methodical, graphical representation of mathematical models of large and complicated chain systems. In this way we can be convinced in the correct composing of models. A high-level programming environment NUT is used as a tool for building modelling and simulation systems. Several modelling and simulation systems have been developed using a
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Naebi, Ahmad, Somayeh Paki Khatibi, Nasser Yousefzadeh Khiabani, and Jahangir Kheyrihassankandi. "A New Programming Language for Microcontroller Using Bond Graph." In 2012 3rd International Conference on Intelligent Systems, Modelling and Simulation (ISMS). IEEE, 2012. http://dx.doi.org/10.1109/isms.2012.84.

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Clark, Ronald, Willem Cronje, and Michael Antonie van Wyk. "Design Optimization of a Hybrid Energy System through Fast Convex Programming." In 2014 5th International Conference on Intelligent Systems, Modelling and Simulation (ISMS). IEEE, 2014. http://dx.doi.org/10.1109/isms.2014.78.

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Qichen Wang and C. Phillips. "Cooperative Path Management for Mobile Systems Based on Adaptive Dynamic Programming." In 2013 UKSim 15th International Conference on Computer Modelling and Simulation (UKSim 2013). IEEE, 2013. http://dx.doi.org/10.1109/uksim.2013.37.

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