Thematische Bibliographien / Machine control system

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Bücher
  4. Buchteile
  5. Konferenzberichte
  6. Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Machine control system“

Autor: Grafiati
Veröffentlicht am 28. Juni 2021
Zuletzt aktualisiert am 29. Juli 2025

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Zeitschriftenartikel zum Thema "Machine control system"

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YAMAMOTO, Takashi, Michihiro OSHIMA, Yoshio YOKOYAMA, and Toshio MIYAGI. "High-precision Grinding System utilizing Machine Vision Control Unit(Advanced machine tool)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 439–42. http://dx.doi.org/10.1299/jsmelem.2005.2.439.

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Chiuso, A., and G. Pillonetto. "System Identification: A Machine Learning Perspective." Annual Review of Control, Robotics, and Autonomous Systems 2, no. 1 (2019): 281–304. http://dx.doi.org/10.1146/annurev-control-053018-023744.

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Estimation of functions from sparse and noisy data is a central theme in machine learning. In the last few years, many algorithms have been developed that exploit Tikhonov regularization theory and reproducing kernel Hilbert spaces. These are the so-called kernel-based methods, which include powerful approaches like regularization networks, support vector machines, and Gaussian regression. Recently, these techniques have also gained popularity in the system identification community. In both linear and nonlinear settings, kernels that incorporate information on dynamic systems, such as the smoo
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Liu, Rui, Gui Xi Liu, Peng Ju Chang, Wei Hua He, and Zeng Jian Huang. "Control System of PDP Lighting Inspection Machine." Applied Mechanics and Materials 130-134 (October 2011): 1903–6. http://dx.doi.org/10.4028/www.scientific.net/amm.130-134.1903.

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The test of panel’s display effect is a key step in the panel production. Lighting inspection machines test the electrical, optical and surface information of Plasma Display Panels (PDPs). This machine is based on a PLC control system and a color analysis system. The PLC system controls a visual positioning system and links to Manufacturing Execution System (MES) and a panel conveyor. This paper considers the structure design and action workflow of the lighting inspection machine. Multi-layer network is built to connect with the whole production system. Optional operation modes are designed in
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Sui, Xiu Lin, Zheng Wei Kong, Jia Tai Zhang, and Xiao Ping Yang. "Study of Virtual Numerical Control Milling Simulation System." Key Engineering Materials 407-408 (February 2009): 174–79. http://dx.doi.org/10.4028/www.scientific.net/kem.407-408.174.

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Virtual numerical control milling simulation system, based on UG, is studied oriented to low utilization of NC machines. A virtual machine tools library, standard fixture library and visual machine tool processing environment were established by the second development techniques of UG and VC++. Through the example of XH715 NC machine center, tool path and motion of miller were simulated separately; at last processing scheme was evaluated and optimized. The experimental results show this system possesses good utility, and the utilization of machine tools could thus be improved.
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Pang, J., C. Chen, C. Wang, Y. Wang, and Y. Shu. "HT-7 machine control system." IEEE Transactions on Nuclear Science 41, no. 1 (1994): 181–83. http://dx.doi.org/10.1109/23.281485.

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Freeman William, T., and D. Weissman Craig. "Hand gesture machine control system." Computer Integrated Manufacturing Systems 10, no. 2 (1997): 175. http://dx.doi.org/10.1016/s0951-5240(97)84336-4.

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Sukharev, Roman, Dmitry Semkin, and Sergey Ignatov. "Autonomous control system road construction machine." Nauchno-tekhnicheskiy vestnik Bryanskogo gosudarstvennogo universiteta 10, no. 1 (2024): 55–64. http://dx.doi.org/10.22281/2413-9920-2024-10-01-55-64.

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The increasing requirements for the accuracy of construction work lead to the need to create modern control systems that will eliminate the human operator from the process of controlling road construction machines, increase the energy efficiency and productivity of these machines, as well as the quality of the finished construction object. The use of unmanned control systems has become an absolute technological break-through. Improving the accuracy of work with the help of unmanned control systems is an urgent and complex area of research. This is due to the need to improve algorithms and impr
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Sorrell, Ethan, Michael E. Rule, and Timothy O'Leary. "Brain–Machine Interfaces: Closed-Loop Control in an Adaptive System." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (2021): 167–89. http://dx.doi.org/10.1146/annurev-control-061720-012348.

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Brain–machine interfaces (BMIs) promise to restore movement and communication in people with paralysis and ultimately allow the human brain to interact seamlessly with external devices, paving the way for a new wave of medical and consumer technology. However, neural activity can adapt and change over time, presenting a substantial challenge for reliable BMI implementation. Large-scale recordings in animal studies now allow us to study how behavioral information is distributed in multiple brain areas, and state-of-the-art interfaces now incorporate models of the brain as a feedback controller.
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Wang, Zifan, Jianming Jian, Xiuying Tang, et al. "Intelligent residual film recovery machine monitoring and control system." Journal of Physics: Conference Series 2704, no. 1 (2024): 012021. http://dx.doi.org/10.1088/1742-6596/2704/1/012021.

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Abstract Domestic residue recovery machines in China still follow the traditional towed mechanical model, lacking automation and intelligent features. Under the key R&D project of Xinjiang Autonomous Region, our team has developed integrated intelligent agricultural machinery for cotton straw crushing and residue recovery. This research covers the monitoring and control system, including PLC control and communication, working parameter monitoring and adjustment, algorithmic control of electro-hydraulic actuators, and human-machine interface display. Compared to traditional models, this mac
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Pereplyotchikov, E. F., I. A. Ryabtsev, Yu N. Lankin, V. F. Semikin, and P. P. Osechkov. "Modernization of control system of A1756 machine for plasma-powder surfacing." Paton Welding Journal 2014, no. 12 (2014): 41–44. http://dx.doi.org/10.15407/tpwj2014.12.09.

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Dissertationen zum Thema "Machine control system"

1

Kanburoglu, Furkan A. "Distributed Control System For Cnc Machine Tools." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12610599/index.pdf.

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&ldquo<br>Numerically Controlled&rdquo<br>(NC) machine tools, which are automatically operated by encoded (digital) commands, are capable of machining components with quality and quantity. Manufacturing industry heavily depends on these machines. Many different control architectures have been adapted in today&rsquo<br>s CNC technology. Centralized control system is quite popular in industry due to its ease of implementation. If the number of controlled axes on a CNC machine tool (&gt<br>3), increases so does the computational burden on the central processors. Hence, more powerful processors
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Lee, Kwangduk Douglas 1970. "Axiomatic development of a machine control system." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8821.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.<br>Includes bibliographical references (leaf 140).<br>Axiomatic Design is presented as a scientific methodology in designing a complex machine control system. As an example, the CMP a machine control system is developed using the Axiomatic Design framework. The machine is a type of semiconductor processing equipment, which requires numerous actuators and sensors and the intelligent control of them to planarize thin layers of wafers. Signal processing modules, control algorithms, sequential process step
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Chen, Xi. "Component-based control system development for agile manufacturing machine systems." Thesis, De Montfort University, 2003. http://hdl.handle.net/2086/13263.

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It is now a common sense that manufactures including machine suppliers and system integrators of the 21 st century will need to compete on global marketplaces, which are frequently shifting and fragmenting, with new technologies continuously emerging. Future production machines and manufacturing systems need to offer the "agility" required in providing responsiveness to product changes and the ability to reconfigure. The primary aim for this research is to advance studies in machine control system design, in the context of the European project VIR-ENG - "Integrated Design, Simulation and Distr
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Yang, Xue Jiao. "Supervisory wide-area control for multi-machine power system." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/supervisory-widearea-control-for-multimachine-power-system(6c0575f9-7b20-4751-9d67-276aaaa4c7b2).html.

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With the increasing demand for electrical power and the growing need for the restructuring of the power industry, electric power systems have become highly complex with inherent complicated dynamics. Therefore, the study of power system stability has continued to receive significant attention from both academic researchers and industrial practitioners. This thesis focuses on supervisory wide-area control for rotor angle stability of multi-machine power systems using Linear Quadratic Gaussian/Loop Transfer Recovery (LQG/LTR) control theory with guaranteed robustness. The supervisory controllers
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Parsons, Erin M. "Control system design for a continuous passive motion machine." Connect to resource, 2010. http://hdl.handle.net/1811/45477.

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Abdulkareem, Alaa Adnan. "Modelling, simulation and control of a PTC machine hall." Thesis, University West, Department of Technology, Mathematics and Computer Science, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hv:diva-1347.

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<p>In this master thesis a flexible manufacturing system for a PTC machine hall has been modelled and simulated using RobCad. This system includes several equipments and machines which have been modelled and arranged to come up with three possible layouts. The machine hall in UW will be moved to a new place in Innovatum (a research area in Trollhättan). The machines were chosen from the existing machine hall according to UW requirements in order not to buy new machines because of economic reasons. The number of cells was also set by UW. The machines and equipments that will be moved are; two C
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Mattie-Suleiman, Eman A. "Instrumentation and control of an industrial sewing machine." Thesis, De Montfort University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.391336.

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曾坤明 and Kwan-ming Tsang. "Decoupling and stabilizing control of multi-machine power systems withstatic VAr compensators." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31211008.

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Thomas, David Andrew. "An adaptive control system for precision cylindrical grinding." Thesis, University of Liverpool, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.243279.

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Gao, Liliang. "Control of three-level 5-phase induction machine drive system." Thesis, University of Strathclyde, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.510860.

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Bücher zum Thema "Machine control system"

1

Sul, Seung-Ki. Control of electric machine drive system. Wiley, 2011.

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Sutton, Robert. Modelling human operators in control system design. Edited by Towill Denis R. Research Studies Press, 1990.

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Hansen, John Paulin. Information nesting in configural interfaces for process control. RisøNational Laboratory, 1992.

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United States. National Aeronautics and Space Administration., ed. Learning fuzzy logic control system. National Aeronautics and Space Administration, 1994.

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Cacciabue, Pietro C. Modelling and simulation of human behaviour in system control. Springer, 1998.

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Cacciabue, Pietro Carlo. Modelling and Simulation of Human Behaviour in System Control. Springer London, 1998.

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service), SpringerLink (Online, ed. Machine Vision Handbook. Springer London, 2012.

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Fähnrich, K. P. Ein System zur wissensbasierten Diagnose an CNC-Werkzeugmaschinen durch den Maschinenbediener. Springer-Verlag, 1990.

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SAE G-10 Committee. and Boeing Company, eds. CNS/ATM: Developing a seamless global operational air traffic management system. Society of Automotive Engineers, 1996.

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1944-, Wise John A., Hopkin V. David, Stager Paul, and NATO Advanced Study Institute and Validation of Complex and Integrated Human-Machine Systems (1992 : Vimeiro, Lisbon, Portugal), eds. Verification and validation of complex systems: Additional human factors issues. Embry-Riddle Aeronautical University Press, 1993.

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Buchteile zum Thema "Machine control system"

1

Huan, Shang, Jiangang Chao, Lan Xie, et al. "Control Simulation to Underwater Manipulator." In Man-Machine-Environment System Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4882-6_38.

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She, Jiahong, Shang Huan, Shaoli Xie, Deli Zhang, Liangliang Han, and Jian Yang. "Control Design to Underwater Robotic Arm." In Man-Machine-Environment System Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4786-5_45.

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Bettega, Jason, Dario Richiedei, and Alberto Trevisani. "Feedforward Control of a Nonlinear Underactuated Multibody System." In Mechanisms and Machine Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15758-5_48.

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Sharma, Sehaj, Prajit Kumar Datta, and Gaurav Bansal. "Machine Learning Based Hospital-Acquired Infection Control System." In Machine Learning and IoT. CRC Press, 2018. http://dx.doi.org/10.1201/9781351029940-12.

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Szulc, Michał, Jerzy Kasprzyk, and Jacek Loska. "Creep Testing Machine Identification for Power System Load Optimization." In Advanced, Contemporary Control. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35170-9_11.

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Bi, Zongjie, Zhaoshuo Tian, Pushuai Shi, and Shiyou Fu. "Design of Turntable Servo Control System Based on Sliding Mode Control Algorithm." In Machine Learning and Intelligent Communications. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73447-7_30.

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Zhang, Yufeng, Xue Wang, Longsen Gao, and Zongbao Liu. "Manipulator Control System Based on Machine Vision." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25128-4_111.

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Dostrašil, Pavel. "Control System and Data Preparation for Kinetic Sculpture Pendulum." In Mechanisms and Machine Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70251-8_20.

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Tian, Zengshan, Mingxiao Wang, Mu Zhou, and Feng Qiu. "Virtual Memory Based Radar Display and Control System." In Machine Learning and Intelligent Communications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52730-7_39.

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Zhang, Lantao, Yongqing Hou, Xi Qu, Jun Ma, and Fanlu Bai. "Research and Prospect of Microbial Control on Space Station." In Man-Machine-Environment System Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4882-6_51.

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Konferenzberichte zum Thema "Machine control system"

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Wang, Chong, Tianqi Tan, Yu Ma, Zhaohui Ding, and Wenwei Fu. "Wearable human-machine integrated control system." In International Conference on Mechatronics and Intelligent Control (ICMIC 2024), edited by Kun Zhang and Pascal Lorenz. SPIE, 2025. https://doi.org/10.1117/12.3045120.

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Lekamge, L. R. S. T., N. P. T. D. Samaranayake, N. V. Weerawarna, D. M. J. C. B. Dissanayake, H. M. S. C. Rathnayake, and Nelum Amarasena. "Integrated Smart Dam Control System Using Machine Learning." In 2024 6th International Conference on Advancements in Computing (ICAC). IEEE, 2024. https://doi.org/10.1109/icac64487.2024.10851035.

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Shah, Aryan Rahul, Ammu Anna Mathew, Karthikeyan V, and Vivekanandan Shanmugasundaram. "Patient Health Classification Using Various Machine Learning Algorithms." In 2024 Control Instrumentation System Conference (CISCON). IEEE, 2024. http://dx.doi.org/10.1109/ciscon62171.2024.10696145.

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Petkar, Taniya. "IoT based Line of Control Monitoring System." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10967893.

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Yang, Xiaowei, Jianguo Wu, Kun Zhang, Peijian Zhang, and Conghua Xie. "Research on machine vision based networked supervisory control system." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737611.

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Salmenpera¨, Pekka, and Juha Miettinen. "Supervised Operation Monitoring and Control System of Rotating Rolls." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-55149.

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The dynamic behavior of rotating machinery depends on the construction and foundation of the machine and in addition of the machine running parameters. By choosing appropriate parameters it is possible to influence considerably on the vibration of the machine. By driving the machine in that kind of an advantageous running window it is possible to minimize the vibration of the machine and to improve the quality of the product, but not to lose the efficiency of the productivity. Machines where the running window is important in maximizing the quality of the product are rotating cylindrical rolls
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Niu, QinZhou, and Yuan Liu. "H-infinity Control Theory in Vehicle Diesel Fuel Injection Pump Control System Design." In 2010 International Conference on Machine Vision and Human-machine Interface. IEEE, 2010. http://dx.doi.org/10.1109/mvhi.2010.99.

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Huang, Xue-Wu, Li-Jun Chen, and Hua-Yao Zheng. "Investigation of Fieldbus Control System in Marine Engine Room Process Control Systems." In 2007 International Conference on Machine Learning and Cybernetics. IEEE, 2007. http://dx.doi.org/10.1109/icmlc.2007.4370232.

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Zibar, Darko, and Francesco Da Ros. "Machine learning techniques for inverse system design and control of photonic systems." In Machine Learning in Photonics, edited by Francesco Ferranti, Mehdi K. Hedayati, and Andrea Fratalocchi. SPIE, 2024. http://dx.doi.org/10.1117/12.3017112.

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Habacher, Michael, Paul O'Leary, Matthew Harker, and Johannes Golser. "Machine vision system for the control of tunnel boring machines." In IS&T/SPIE Electronic Imaging, edited by Philip R. Bingham and Edmund Y. Lam. SPIE, 2013. http://dx.doi.org/10.1117/12.2003847.

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Berichte der Organisationen zum Thema "Machine control system"

1

Miller, D. J., and C. S. Loucks. An intelligent CNC machine control system architecture. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/399679.

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Fishman, Douglas. The High Level Machine-tool Control System. National Bureau of Standards, 1988. http://dx.doi.org/10.6028/nbs.ir.88-3836.

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Abdel-Gwad, A., A. Aguirre, and V. Van Note. SoW for Moore Machine Control System Refurbishment. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/1994036.

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Chassin, David P. The Abstract Machine Model for Transaction-based System Control. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/969749.

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Cary, Dakota, and Daniel Cebul. Destructive Cyber Operations and Machine Learning. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/2020ca003.

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Machine learning may provide cyber attackers with the means to execute more effective and more destructive attacks against industrial control systems. As new ML tools are developed, CSET discusses the ways in which attackers may deploy these tools and the most effective avenues for industrial system defenders to respond.
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Domer, G. A. Modification of the logic and control system for the 80-ounce injection molding machine. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/5050653.

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Konsam, Manis Kumar, Amanda Thounajam, Prasad Vaidya, Gopikrishna A, Uthej Dalavai, and Yashima Jain. Machine Learning-Enhanced Control System for Optimized Ceiling Fan and Air Conditioner Operation for Thermal Comfort. Indian Institute for Human Settlements, 2024. http://dx.doi.org/10.24943/mlcsocfacotc6.2023.

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This paper proposes and tests the implementation of a sustainable cooling approach that uses a machine learning model to predict operative temperatures, and an automated control sequence that prioritises ceiling fans over air conditioners. The robustness of the machine learning model (MLM) is tested by comparing its prediction with that of a straight-line model (SLM) using the metrics of Mean Bias Error (MBE) and Root Mean Squared Error (RMSE). This comparison is done across several rooms to see how each prediction method performs when the conditions are different from those of the original ro
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Truitt, R. W. Human-machine interface (HMI) report for 241-SY-101 data acquisition [and control] system (DACS) upgrade study. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/353243.

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Froehlich, D. P., and J. A. Schumacher. Develop a field grid system for yield mapping and machine control. Quarterly report, January 1, 1995--March 31, 1995. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/33081.

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Hart, F., and J. Windish. Develop a field grid system for yield mapping and machine control. Quarterly report, July 1, 1995--September 30, 1995. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/108125.

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