Relevant bibliographies by topics / Intelligent Controls

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Intelligent Controls'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

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Journal articles on the topic "Intelligent Controls"

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Christodoulou, Manolis. "Intelligent Controls." Journal of Intelligent & Robotic Systems 12, no. 3 (October 1995): 195–96. http://dx.doi.org/10.1007/bf01262960.

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John, R. W., and A. L. Dexter. "Intelligent controls for building services." Building Services Engineering Research and Technology 10, no. 4 (November 1989): 131–41. http://dx.doi.org/10.1177/014362448901000401.

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Wei, Ying-Jyi Paul. "Intelligent control law tuning for AIAA controls design challenge." Journal of Guidance, Control, and Dynamics 17, no. 4 (July 1994): 753–58. http://dx.doi.org/10.2514/3.21264.

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Schlechtendahl, J., S. Braun, P. Schraml, E. Abele, U. Heisel, A. Verl, and A. Lechler. "Modellbasierte, energieoptimale Maschinensteuerung*/Model-based, energy-optimal production control - Reduction of energy consumption over multiple layers within the control hierarchy." wt Werkstattstechnik online 105, no. 06 (2015): 440–44. http://dx.doi.org/10.37544/1436-4980-2015-06-92.

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Der Einfluss moderner Werkzeugmaschinen auf die Umwelt basiert größtenteils auf deren Energieverbrauch im Produktivbetrieb. Um diesen Energieverbrauch zu senken, bietet sich der Einsatz von modellbasierten Strategien an. Für die Nutzung dieser Strategien in Werkzeugmaschinensteuerungen müssen modellbasierte Optimierer und Steuerungsinformationen zur intelligenten Energieverbrauchssteuerung verknüpft werden. In diesem Fachbeitrag wird ein Ansatz für eine intelligente Energieverbrauchssteuerung vorgestellt sowie anhand von Prozess- und Komponentenoptimierern validiert. Teil 1 des Fachbeitrags ist erschienen in der wt-Ausgabe 5-2015 auf den Seiten 324–328.   Modern machine tools mainly affect the environment by their energy consumption during operational life. Model-based strategies could be used for decreasing the energy consumption of machine tools. To enable the use of these strategies in machine controls, model-based optimizers and control information need to be connected to an intelligent energy controller. This paper introduces an approach to an intelligent energy controller for machine tools, validated by process and component optimizers.
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Opdenbosch, Patrick, Nader Sadegh, and Wayne Book. "Intelligent controls for electro-hydraulic poppet valves." Control Engineering Practice 21, no. 6 (June 2013): 789–96. http://dx.doi.org/10.1016/j.conengprac.2013.02.008.

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Brovko, Oleg, Alexey Eliseev, Vladimir Kekelidze, Vladimir Korenkov, Dmitry Monahov, Andrey Reshetnikov, Gennadii Reshetnikov, and Sergey Ulyanov. "Necessity of intelligent control systems application in experimental nuclear physics complexes (NICA type).PT.I: Problems of unforeseen situations." System Analysis in Science and Education, no. 4 (2019) (2019): 32–57. http://dx.doi.org/10.37005/2071-9612-2019-4-32-57.

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In the article (Part I) the necessity of application of end-to-end quantum technologies of intelligent computing in problems of structure elements control of complex experimental accelerator complex NICA is analyzed. Given a description of possible unforeseen situations, their classification is given to include adjustments to the decision-making application of production rules, logic knowledge bases of intelligent control systems based on emerging information risk increment. In the second part (Part II) the proposed two-level intelligent control system, a physical experimental setup of the NICA complex, in which the lower Executive level is a traditional control system based on expert control using the Tango control system Controls, while the upper (intelligent) level control actions are generated using the methods of quantum end-to-end IT design quantum fuzzy controller. Part II presents the QSCIT (Quantum Soft Computational Intelligence Toolkit), based on soft and quantum computing, to design robust knowledge bases in self-organizing intelligent control systems.
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Azahar, Kaiyisah Baiduri, Ericka Ensimau Sekudan, and Ahmad Mirza Azhar. "Intelligent Egg Incubator." International Journal of Recent Technology and Applied Science 2, no. 2 (September 27, 2020): 91–102. http://dx.doi.org/10.36079/lamintang.ijortas-0202.129.

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This research presents the design and development of a chicken egg incubator. The aim is to design and construct an “Intelligent Egg Incubator” that can hatch chicken eggs automatically. In the design, author used a temperature control system that controls the temperature of the incubator. This system consists of a temperature sensor, heating and cooling elements and a controller. If the temperature of the incubator exceeds a certain value, the cooling unit will operate to reduce the temperature while if the temperature goes below another threshold value, the heating element will start to operate to increase the temperature. Furthermore, author used a motion sensor to detect the movements of the eggs. If there is a movement inside the incubator, the owner of the incubator will get the notification about the conditions of the eggs
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Rong, Jing. "The Design of Intelligent Street Lighting Control System." Advanced Materials Research 671-674 (March 2013): 2941–45. http://dx.doi.org/10.4028/www.scientific.net/amr.671-674.2941.

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The paper puts forward a modification plan which combines the wireless communication network with power line communication to reduce energy waste in the city lighting system at night. The system framework is divided into three layers, the backend server controls the centralized controllers through the core network; each centralized controller controls the lamps through the access network; node controller on each street light works as a terminal which controls the light according to the commend receives from the centralized controllers through PLC. The system combines wireless communications, power line carrier, LED circuit constant current drive with PWM stepless dimming technology. The application results show that the system can reduce the electric energy consumption obviously, and the intelligent street lamps operate stably and reliably.
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Tang, Baoping. "Research on mechanical measurement-oriented intelligent virtual controls." Chinese Journal of Mechanical Engineering (English Edition) 17, no. 03 (2004): 356. http://dx.doi.org/10.3901/cjme.2004.03.356.

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Greshnikov, I. I. "Gaze Control Function Implementation in the Aircraft Cockpit Displays and Controls." INFORMACIONNYE TEHNOLOGII 27, no. 8 (August 11, 2021): 445–48. http://dx.doi.org/10.17587/it.27.445-448.

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The paper analyzes modern solutions applicable to advanced cockpit development using the gaze control function. Based on the analysis, the conclusion is made about the practicability of using the gaze control function and the intelligent information system is being developed for testing this function on the basis of universal cockpit prototyping bench.
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Dissertations / Theses on the topic "Intelligent Controls"

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Wilmot, Timothy Allen Jr. "Intelligent Controls for a Semi-Active Hydraulic Prosthetic Knee." Cleveland State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=csu1315531357.

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Chiu, Kuan-Shiu. "Adaptive optimization of intelligent flow control." Thesis, University of Sunderland, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.288014.

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Maughan, Douglas Spencer. "Robust Intelligent Sensing and Control Multi Agent Analysis Platform for Research and Education." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/4965.

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The aim of this thesis is the development and implementation of a controlled testing platform for the Robust Intelligent Sensing and Controls (RISC) Lab at Utah State University (USU). This will be an open source adaptable expandable robotics platform usable for both education and research. This differs from the many other platforms developed in that the entire platform software will be made open source. This open source software will encourage collaboration among other universities and enable researchers to essentially pick up where others have left off without the necessity of replicating months or even years of work. The expected results of this research will create a foundation for diverse robotics investigation at USU as well as enable attempts at novel methods of control, estimation and optimization. This will also contribute a complete software testbed setup to the already vibrant robotics open source research community. This thesis first outlines the platform setup and novel developments therein. The second stage provides an example of how this has been used in education, providing an example curriculum implementing modern control techniques. The third section provides some exploratory research in trajectory control and state estimation of the tip of an inverted pendulum atop a small unmanned aerial vehicle as well as bearing-only cooperative localization experimentation. Finally, a conclusion and future work is discussed.
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Liu, Yukang. "Virtualized Welding Based Learning of Human Welder Behaviors for Intelligent Robotic Welding." UKnowledge, 2014. http://uknowledge.uky.edu/ece_etds/51.

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Combining human welder (with intelligence and sensing versatility) and automated welding robots (with precision and consistency) can lead to next generation intelligent welding systems. In this dissertation intelligent welding robots are developed by process modeling / control method and learning the human welder behavior. Weld penetration and 3D weld pool surface are first accurately controlled for an automated Gas Tungsten Arc Welding (GTAW) machine. Closed-form model predictive control (MPC) algorithm is derived for real-time welding applications. Skilled welder response to 3D weld pool surface by adjusting the welding current is then modeled using Adaptive Neuro-Fuzzy Inference System (ANFIS), and compared to the novice welder. Automated welding experiments confirm the effectiveness of the proposed human response model. A virtualized welding system is then developed that enables transferring the human knowledge into a welding robot. The learning of human welder movement (i.e., welding speed) is first realized with Virtual Reality (VR) enhancement using iterative K-means based local ANFIS modeling. As a separate effort, the learning is performed without VR enhancement utilizing a fuzzy classifier to rank the data and only preserve the high ranking “correct” response. The trained supervised ANFIS model is transferred to the welding robot and the performance of the controller is examined. A fuzzy weighting based data fusion approach to combine multiple machine and human intelligent models is proposed. The data fusion model can outperform individual machine-based control algorithm and welder intelligence-based models (with and without VR enhancement). Finally a data-driven approach is proposed to model human welder adjustments in 3D (including welding speed, arc length, and torch orientations). Teleoperated training experiments are conducted in which a human welder tries to adjust the torch movements in 3D based on his observation on the real-time weld pool image feedback. The data is off-line rated by the welder and a welder rating system is synthesized. ANFIS model is then proposed to correlate the 3D weld pool characteristic parameters and welder’s torch movements. A foundation is thus established to rapidly extract human intelligence and transfer such intelligence into welding robots.
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Sabourin, Nicole Tan. "The effects of connected lighting on lighting controls and design." Kansas State University, 2017. http://hdl.handle.net/2097/35481.

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Master of Science
Department of Architectural Engineering and Construction Science
Fred L. Hasler
The Internet of Things (IoT) is rapidly growing and is starting to be incorporated into commercial buildings. One of the ways that the IoT is being used in buildings is connected lighting, also referred to as smart lighting. Connected lighting allows for communication between the lighting system, people, the environment, and other devices. This paper will focus on connected lighting and its effect on lighting controls and design. The IoT is expected to see substantial growth in the next few years and the growth of connected devices will have a huge impact on the lighting industry as connected lighting systems will be installed in more commercial buildings. The shift to solid state lighting (SSL) in recent years has brought the transition from conventional lighting controls to connected lighting controls. For this shift to be successful, issues with interoperability, security and reliability will need to be overcome. Connected lighting systems on the market are using both wired and wireless technologies. Power over Ethernet (PoE) and wireless technologies such as ZigBee and Bluetooth Smart are currently being incorporated into connected lighting systems. The introduction of these technologies is changing the way that lighting control systems are designed and installed. Products such as fixture-integrated sensors and wireless devices are also being used in connected lighting systems. These products, along with the wired and wireless technologies, are changing lighting control system configurations. Lighting design will also be affected by connected lighting systems. New features including color-tunability and indoor positioning will be used to enhance the lighting system and improve occupant health. Also, energy code compliance will be easier since connected lighting controls will be mostly software-based and can be reprogrammed. Connected lighting systems will be integrated into other building systems such as heating, ventilating, and air conditioning systems or security systems and will also be used in a variety of applications. Connected lighting systems will greatly affect both lighting controls and design of lighting control systems. This paper introduces connected lighting and is intended for those who are not familiar with its design, applications, and implementation.
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Ma, Tan. "Hybrid Power System Intelligent Operation and Protection Involving Plug-in Electric Vehicles." FIU Digital Commons, 2015. http://digitalcommons.fiu.edu/etd/1760.

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Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.
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Hanlon, Nicholas P. "Simulation Research Framework with Embedded Intelligent Algorithms for Analysis of Multi-Target, Multi-Sensor, High-Cluttered Environments." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1460730865.

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Wilson, Michael Thomas. "Technology advancement in intelligent buildings a through preplanning process pertaining to long-term maintainability /." Thesis, Available online, Georgia Institute of Technology, 2004:, 2004. http://etd.gatech.edu/theses/available/etd-08172004-150143/unrestricted/wilson%5Fmichael%5Ft%5F200412%5Fms.pdf.

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Thesis (M.S.)--Building Construction, Georgia Institute of Technology, 2005.
Dr. Felix T. Uhlik III, Committee Member ; Mr. Cliff Stern, Committee Member ; Dr. Rita Oberle, Committee Member ; Ms. Kathy O. Roper, Committee Chair. Includes bibliographical references.
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Valdes, Diaz Didier M. "Integrated information and traffic control strategies for congested urban freeway corridors /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Thomas, Kim. "Incident detection on arterials using neural network data fusion of simulated probe vehicle and loop detector data /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18433.pdf.

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Books on the topic "Intelligent Controls"

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Bebenik, Kevin. Intelligent transportation systems and road capacity. Ottawa: Transportation Association of Canada = Association des transports du Canada, 1999.

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Perspectives on intelligent transportation systems (ITS). New York: Springer, 2005.

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IVHS America. National Working Group on IVHS Safety and Human Factors. Intelligent vehicle-highway systems (IVHS) safety and human factors considerations. Washington, D.C: IVHS America, 1992.

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IVHS America. National Working Group on IVHS Safety and Human Factors. Intelligent vehicle-highway systems (IVHS) safety and human factors considerations. Washington, D.C: IVHS America, 1992.

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Ishimaru, John M. North Seattle advanced traffic management system (NSATMS) project evaluation. [Olympia, Wash.]: Washington State Dept. of Transportation, 2002.

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Pushkin, Kachroo, ed. Incident management in intelligent transportation systems. Boston: Artech House, 1999.

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National Working Group on IVHS Safety and Human Factors. Intelligent vehicle-highway systems (IVHS) safety and human factors considerations. Washington, D.C: IVHS America, 1992.

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United States. Congress. Senate. Committee on Commerce, Science, and Transportation. Intelligent vehicle-highway systems program and commercial motor vehicles: Hearing before the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Third Congress, first session, October 19, 1993. Washington: U.S. G.P.O., 1994.

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United States. Congress. House. Committee on Science, Space, and Technology. Subcommittee on Investigations and Oversight. Intelligent vehicle highway systems: Hearing before the Subcommittee on Investigations and Oversight of the Committee on Science, Space, and Technology, U.S. House of Representatives, One Hundred Third Congress, first session, November 10, 1993. Washington: U.S. G.P.O., 1994.

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Duo che xing dong tai jiao tong fen pei wen ti yan jiu. Beijing: Ke xue chu ban she, 2013.

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Book chapters on the topic "Intelligent Controls"

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De Schutter, Bart, Jeroen Ploeg, Lakshmi Dhevi Baskar, Gerrit Naus, and Henk Nijmeijer. "Hierarchical, Intelligent and Automatic Controls." In Handbook of Intelligent Vehicles, 81–116. London: Springer London, 2012. http://dx.doi.org/10.1007/978-0-85729-085-4_5.

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Tzafestas, S. G. "Introduction: Overview of Intelligent Controls." In Methods and Applications of Intelligent Control, 3–23. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5498-7_1.

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Taghavipour, Amir, Mahyar Vajedi, and Nasser L. Azad. "Route-Based Supervisory Controls." In Intelligent Control of Connected Plug-in Hybrid Electric Vehicles, 145–67. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00314-2_8.

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Li, Zhijun, and Shuzhi Sam Ge. "Balancing and Posture Controls for Biped Robots with Unmodelled Dynamics." In Intelligent Robotics and Applications, 56–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33509-9_6.

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Feddema, John T., and David A. Schoenwald. "Stability Analysis of Decentralized Cooperative Controls." In Multi-Robot Systems: From Swarms to Intelligent Automata, 113–22. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-017-2376-3_12.

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Cottin, Tim, Eugen Nordheimer, Achim Wagner, and Essameddin Badreddin. "Gaze-Based Human-SmartHome-Interaction by Augmented Reality Controls." In Advances in Intelligent Systems and Computing, 378–85. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49058-8_41.

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Fingerle, Robert, Lars Krause, Hugo Tausch, and Carsten Wittenberg. "User-Centered Design and Evaluation of Smartphone-Controls for the Movement Control of Mobile Platforms." In Advances in Intelligent Systems and Computing, 87–98. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60384-1_9.

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Dimirovski, Georgi M. "Learning Intelligent Controls in High Speed Networks: Synergies of Computational Intelligence with Control and Q-Learning Theories." In Studies in Computational Intelligence, 111–39. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27267-2_4.

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Luo, Jinming, and Georgi M. Dimirovski. "Intelligent Controls for Switched Fuzzy Systems: Synthesis via Nonstandard Lyapunov Functions." In Recent Contributions in Intelligent Systems, 115–41. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41438-6_8.

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Lopez-Rojas, Edgar A., and Camille Barneaud. "Advantages of the PaySim Simulator for Improving Financial Fraud Controls." In Advances in Intelligent Systems and Computing, 727–36. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22868-2_51.

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Conference papers on the topic "Intelligent Controls"

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Pfeufer, Thomas, and Rolf Isermann. "Intelligent electromechanical actuators." In Aerospace/Defense Sensing and Controls, edited by Robert Lee Murrer, Jr. SPIE, 1996. http://dx.doi.org/10.1117/12.241128.

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Chamy, Lara Al, Mohamad Saad El Dine, Abd El Kader El Rafeii, and Ahmad Rafihi. "Infinity of controls with intelligent robot remote control." In 2017 Sensors Networks Smart and Emerging Technologies (SENSET). IEEE, 2017. http://dx.doi.org/10.1109/senset.2017.8125036.

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Swain, Nikunja K., James A. Anderson, and A. M. Hasanul-Basher. "Intelligent sensor integrated system." In Aerospace/Defense Sensing and Controls, edited by Ivan Kadar. SPIE, 1998. http://dx.doi.org/10.1117/12.327113.

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Garg, Sanjay, Klaus Schadow, Wolfgang Horn, Hugo Pfoertner, and Ion Stiharu. "Sensor and Actuator Needs for More Intelligent Gas Turbine Engines." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-22685.

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This paper provides an overview of the controls and diagnostics technologies, that are seen as critical for more intelligent gas turbine engines (GTE), with an emphasis on the sensor and actuator technologies that need to be developed for the controls and diagnostics implementation. The objective of the paper is to help the “Customers” of advanced technologies, defense acquisition and aerospace research agencies, understand the state-of-the-art of intelligent GTE technologies, and help the “Researchers” and “Technology Developers” for GTE sensors and actuators identify what technologies need to be developed to enable the “Intelligent GTE” concepts and focus their research efforts on closing the technology gap. To keep the effort manageable, the focus of the paper is on “On-Board Intelligence” to enable safe and efficient operation of the engine over its life time, with an emphasis on gas path performance.
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Ferreira Brega, Jose R., Manoel H. Alba Soria, Joao F. Marar, and Antonio C. Sementille. "Intelligent system for pavement management." In Aerospace/Defense Sensing and Controls, edited by Steven K. Rogers, David B. Fogel, James C. Bezdek, and Bruno Bosacchi. SPIE, 1998. http://dx.doi.org/10.1117/12.304849.

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WEI, YING-JYI. "Intelligent control law tuning for AIAA Controls Design Challenge." In Astrodynamics Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1992. http://dx.doi.org/10.2514/6.1992-4631.

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Huang, En-Hsin, and Tzilla Elrad. "Reflective controls for intelligent distributed objects." In the 2001 ACM symposium. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/372202.372469.

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Saridis, George N., and Kimon P. Valavanis. "On The Theory Of Intelligent Controls." In Robotics and IECON '87 Conferences, edited by David P. Casasent and Ernest L. Hall. SPIE, 1988. http://dx.doi.org/10.1117/12.942789.

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Braunsteiner, Arnold, Georg Hutflesz, Thomas Gruenberger, and Markus Bohrer. "Sensors and controls for intelligent machining." In Photonics East '99, edited by George K. Knopf, Patrick F. Muir, and Peter E. Orban. SPIE, 1999. http://dx.doi.org/10.1117/12.371169.

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Byrd, Katherine A., Bart Smith, Doug Allen, Norman Morris, Charles A. Bjork, Jr., Kim Deal-Giblin, and John A. Rushing. "Intelligent processing techniques for sensor fusion." In Aerospace/Defense Sensing and Controls, edited by Belur V. Dasarathy. SPIE, 1998. http://dx.doi.org/10.1117/12.303669.

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Reports on the topic "Intelligent Controls"

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Li, Haorong, Yong Cho, and Dongming Peng. Intelligent Controls for Net-Zero Energy Buildings. Office of Scientific and Technical Information (OSTI), October 2011. http://dx.doi.org/10.2172/1084258.

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Ghiu, Camil. High Flux Commercial Illumination Solution with Intelligent Controls. Office of Scientific and Technical Information (OSTI), April 2012. http://dx.doi.org/10.2172/1051491.

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Morse, A. S. Intelligent Distributed Control. Fort Belvoir, VA: Defense Technical Information Center, August 2012. http://dx.doi.org/10.21236/ada567139.

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Morse, A. S. Intelligent Control of Uncertain Systems. Fort Belvoir, VA: Defense Technical Information Center, March 2000. http://dx.doi.org/10.21236/ada375427.

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Connors, John J., Kevin Hill, David Hanekamp, William F. Haley, Robert J. Gallagher, Craig Gowin, Arthur R. Farrar, et al. Sensor fusion for intelligent process control. Office of Scientific and Technical Information (OSTI), August 2004. http://dx.doi.org/10.2172/919114.

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Ramamoorthy, P. A. Intelligent Signal Processing for Active Control. Fort Belvoir, VA: Defense Technical Information Center, June 1992. http://dx.doi.org/10.21236/ada252232.

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7

Stolarik, Brian. Intelligent Flight Control Simulation Research Program. Fort Belvoir, VA: Defense Technical Information Center, February 2007. http://dx.doi.org/10.21236/ada470308.

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

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Klevans, E. H. Intelligent distributed control for nuclear power plants. Office of Scientific and Technical Information (OSTI), September 1991. http://dx.doi.org/10.2172/10104980.

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Klevans, E. H., R. M. Edwards, A. Ray, K. Y. Lee, H. E. :. Chavez, C. M. Garcia, J. A. Turso, and A. BenAbdennour. Intelligent distributed control for nuclear power plants. Office of Scientific and Technical Information (OSTI), January 1991. http://dx.doi.org/10.2172/6909089.

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