Relevant bibliographies by topics / Guidance and control

Academic literature on the topic 'Guidance and control'

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Published: 4 June 2021
Last updated: 6 September 2023

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Journal articles on the topic "Guidance and control"

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Luque, Juan C. Cutipa, and Decio Crisol Donha. "AUV Robust Guidance Control*." IFAC Proceedings Volumes 41, no. 1 (2008): 85–90. http://dx.doi.org/10.3182/20080408-3-ie-4914.00016.

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Seshadri, V. "Control Systems And Guidance." IETE Journal of Education 27, no. 1 (January 1986): 10–14. http://dx.doi.org/10.1080/09747338.1986.11436092.

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Siouris,, George M. "Missile Guidance and Control Systems." Applied Mechanics Reviews 57, no. 6 (November 1, 2004): B32. http://dx.doi.org/10.1115/1.1849174.

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Qazizadeh, Alireza, Sebastian Stichel, and Hamid Reza Feyzmahdavian. "Wheelset curving guidance usingH∞control." Vehicle System Dynamics 56, no. 3 (November 7, 2017): 461–84. http://dx.doi.org/10.1080/00423114.2017.1391396.

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MIYAZAWA, Yoshikazu, Tatsushi IZUMI, Shigeru ASAI, and Masaru OKA. "Guidance and Control of ALFLEX." Journal of the Japan Society for Aeronautical and Space Sciences 46, no. 528 (1998): 18–28. http://dx.doi.org/10.2322/jjsass1969.46.18.

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O’Hara, John, James Higgins, and Stephen Fleger. "Control Room Design Review Guidance." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 58, no. 1 (September 2014): 2250–54. http://dx.doi.org/10.1177/1541931214581469.

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Sekkides, Onisillos. "ECDC issues chlamydia control guidance." Lancet Infectious Diseases 9, no. 9 (September 2009): 530. http://dx.doi.org/10.1016/s1473-3099(09)70215-4.

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Todd, Patrick, and Neal A. Tognazzini. "A PROBLEM FOR GUIDANCE CONTROL." Philosophical Quarterly 58, no. 233 (October 2008): 685–92. http://dx.doi.org/10.1111/j.1467-9213.2008.576.x.

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Feng, Mei, Chan Li, and Sarah McVay. "Internal control and management guidance." Journal of Accounting and Economics 48, no. 2-3 (December 2009): 190–209. http://dx.doi.org/10.1016/j.jacceco.2009.09.004.

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Lin, Chih-Min, Chun-Fei Hsu, Shing-Kuo Chang, and Rong-Jong Wai. "GUIDANCE LAW EVALUATION FOR MISSILE GUIDANCE SYSTEMS." Asian Journal of Control 2, no. 4 (October 22, 2008): 243–50. http://dx.doi.org/10.1111/j.1934-6093.2000.tb00029.x.

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Dissertations / Theses on the topic "Guidance and control"

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Çelik, Ugurcan. "Robust Booster Landing Guidance/Control." Thesis, KTH, Optimeringslära och systemteori, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279684.

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The space industry and the technological developments regarding space exploration hasn’t been this popular since the first moon landing. The privatization of space exploration and the vertical landing rockets made rocket science mainstream again. While being able to reuse rockets is efficient both in terms of profitability and popularity, these developments are still in their early stages. Vertical landing has challenges that, if neglected, can cause disastrous consequences. The existing studies on the matter usually don’t account for aerodynamics forces and corresponding controls, which results in higher fuel consumption thus lessening the economical benefits of vertical landing. Similar problems have been tackled in studies not regarding booster landings but regarding planetary landings. And while multiple solutions have been proposed for these problems regarding planetary landings, the fact that the reinforcement learning concepts work well and provide robustness made them a valid candidate for applying to booster landings. In this study, we focus on developing a vertical booster descent guidance and control law that’s robust by applying reinforcement learning concept. Since reinforcement learning method that is chosen requires solving Optimal Control Problems (OCP), we also designed and developed an OCP solver software. The robustness of resulting hybrid guidance and control policy will be examined against various different uncertainties including but not limited to wind, delay and aerodynamic uncertainty.
Rymdindustrin och den tekniska utvecklingen av rymdutforskningen har inte varit så populär sedan den första månlandningen. Privatiseringen av utforskningen av rymden och de vertikala landningsraketerna medförde att raketvetenskapen återkom som en viktig huvudfråga igen. Även om det är effektivt att återanvända raketer i form av lönsamhet och popularitet, är denna utveckling fortfarande i sina tidiga stadier. Vertikal landning har utmaningar som, om de försummas, kan orsaka katastrofala konsekvenser. De befintliga studierna i frågan redovisar vanligtvis inte aerodynamikkrafter och motsvarande regulatorer, vilket resulterar i högre bränsleförbrukning som minskar de ekonomiska fördelarna med vertikal landning. Liknande problem har hanterats i studier som inte avsåg boosterlandningar utan om planetariska landningar. Även om flera lösningar har föreslagits för dessa problem beträffande planetariska landningar, det faktum att förstärkningsinlärningskonceptet fungerar bra och ger robusthet gjorde dem till en giltig kandidat för att ansöka om boosterlandningar. I den här studien fokuserar vi på att utveckla en lagstiftning för styrning av vertikala booster-nedstigningar som är robust genom att tillämpa koncepten inom förstärkningsinlärning. Ef- tersom förstärkt inlärningsmetod som väljs kräver lösning av optimala kontrollproblem (OCP), designade och utvecklade vi också en OCP-lösningsmjukvara. Robustheten för resulterande hybridstyrning och kontrollpolicy kommer att undersökas mot olika osäkerheter inklusive, men inte begränsat till vind, fördröjning och aerodynamisk osäkerhet.
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Kørte, Steffen Østensjø. "Guidance & Control Strategies for UUVs." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for marin teknikk, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-16228.

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Focus on safety and effectiveness in the oil and gas industry has increased the need for advanced control system for underwater vehicles. For remotely operated vehicles (ROVs) effectiveness when conducting deep sea operation is extremely critical both concerning safety and cost. For AUVs conducting survey missions, energy and collision avoidance are critical factors. A control system for ROV Minerva is being developed through the AUR-Lab at the Institute of Marine Technology at NTNU. Several guidance features have been investigated, with respect to different mission the ROV should be able to do. A guidance system has been developed, where basic functions such as a DP system with station keeping and trajectory tracking was the focus of the project thesis of the author. More advanced functionality with respect to path following has been developed, where focus have been set on different strategies to apply when the ROV is following a path. Simulations based on different strategies for following a lawnmower pattern have been simulated and evaluated with respect to time, energy and control objective. Full scale experiments with the ROV Minerva show that especially the forward speed versus arc radius is an important issue. The results show that the ROV is able to follow a path made out of straight lines and circular arcs, and particularly lawnmower patterns. For an underwater vehicle to be able to operate autonomously, stationary and dynamic obstacles have to be taken into account. A collision avoidance system based on local collision avoidance algorithms has been implemented, where focus has been on reactivity with respect to unmapped obstacles. The collision avoidance system has been through initial full scale tests with ROV Minerva, and the result are promising.
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Ilg, Mark Dean Chang Bor-Chin. "Guidance, navigation, and control for munitions /." Philadelphia, Pa. : Drexel University, 2008. http://hdl.handle.net/1860/2831.

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Rubí, Perelló Bertomeu. "Guidance, navigation and control of multirotors." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/673068.

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This thesis presents contributions to the Guidance, Navigation and Control (GNC) systems for multirotor vehicles by applying and developing diverse control techniques and machine learning theory with innovative results. The aim of the thesis is to obtain a GNC system able to make the vehicle follow predefined paths while avoiding obstacles in the vehicle's route. The system must be adaptable to different paths, situations and missions, reducing the tuning effort and parametrisation of the proposed approaches. The multirotor platform, formed by the Asctec Hummingbird quadrotor vehicle, is studied and described in detail. A complete mathematical model is obtained and a freely available and open simulation platform is built. Furthermore, an autopilot controller is designed and implemented in the real platform. The control part is focused on the path following problem. That is, following a predefined path in space without any time constraint. Diverse control-oriented and geometrical algorithms are studied, implemented and compared. Then, the geometrical algorithms are improved by obtaining adaptive approaches that do not need any parameter tuning. The adaptive geometrical approaches are developed by means of Neural Networks. To end up, a deep reinforcement learning approach is developed to solve the path following problem. This approach implements the Deep Deterministic Policy Gradient algorithm. The resulting approach is trained in a realistic multirotor simulator and tested in real experiments with success. The proposed approach is able to accurately follow a path while adapting the vehicle's velocity depending on the path's shape. In the navigation part, an obstacle detection system based on the use of a LIDAR sensor is implemented. A model of the sensor is derived and included in the simulator. Moreover, an approach for treating the sensor data to eliminate the possible ground detections is developed. The guidance part is focused on the reactive path planning problem. That is, a path planning algorithm that is able to re-plan the trajectory online if an unexpected event, such as detecting an obstacle in the vehicle's route, occurs. A deep reinforcement learning approach for the reactive obstacle avoidance problem is developed. This approach implements the Deep Deterministic Policy Gradient algorithm. The developed deep reinforcement learning agent is trained and tested in the realistic simulation platform. This agent is combined with the path following agent and the rest of the elements developed in the thesis obtaining a GNC system that is able to follow different types of paths while avoiding obstacle in the vehicle's route.
Aquesta tesi doctoral presenta diverses contribucions relaciones amb els sistemes de Guiat, Navegació i Control (GNC) per a vehicles multirrotor, aplicant i desenvolupant diverses tècniques de control i de machine learning amb resultats innovadors. L'objectiu principal de la tesi és obtenir un sistema de GNC capaç de dirigir el vehicle perquè segueixi una trajectòria predefinida mentre evita els obstacles que puguin aparèixer en el recorregut del vehicle. El sistema ha de ser adaptable a diferents trajectòries, situacions i missions, reduint l'esforç realitzat en l'ajust i la parametrització dels mètodes proposats. La plataforma experimental, formada pel cuadricòpter Asctec Hummingbird, s'estudia i es descriu en detall. S'obté un model matemàtic complet de la plataforma i es desenvolupa una eina de simulació, la qual és de codi lliure. A més, es dissenya un controlador autopilot i s'implementa en la plataforma real. La part de control està enfocada al problema de path following. En aquest problema, el vehicle ha de seguir una trajectòria predefinida en l'espai sense cap tipus de restricció temporal. S'estudien, s'implementen i es comparen diversos algoritmes de control i geomètrics de path following. Després, es milloren els algoritmes geomètrics usant xarxes neuronals per convertirlos en algoritmes adaptatius. Per finalitzar, es desenvolupa un mètode de path following basat en tècniques d'aprenentatge per reforç profund (deep Reinforcement learning). Aquest mètode implementa l'algoritme Deep Deterministic Policy Gradient. L'agent intel. ligent resultant és entrenat en un simulador realista de multirotors i validat en la plataforma experimental real amb èxit. Els resultats mostren que l'agent és capaç de seguir de forma precisa la trajectòria de referència adaptant la velocitat del vehicle segons la curvatura del recorregut. A la part de navegació, s'implementa un sistema de detecció d'obstacles basat en l'ús d'un sensor LIDAR. Es deriva un model del sensor i aquest s'inclou en el simulador. A més, es desenvolupa un mètode per tractar les mesures del sensor per eliminar les possibles deteccions del terra. Pel que fa a la part de guiatge, aquesta està focalitzada en el problema de reactive path planning. És a dir, un algoritme de planificació de trajectòria que és capaç de re-planejar el recorregut del vehicle a l'instant si algun esdeveniment inesperat ocorre, com ho és la detecció d'un obstacle en el recorregut del vehicle. Es desenvolupa un mètode basat en aprenentatge per reforç profund per l'evasió d'obstacles. Aquest mètode implementa l'algoritme Deep Deterministic Policy Gradient. L'agent d'aprenentatge per reforç s'entrena i valida en un simulador de multirotors realista. Aquest agent es combina amb l'agent de path following i la resta d'elements desenvolupats en la tesi per obtenir un sistema GNC capaç de seguir diferents tipus de trajectòries, evadint els obstacles que estiguin en el recorregut del vehicle.
Esta tesis doctoral presenta varias contribuciones relacionas con los sistemas de Guiado, Navegación y Control (GNC) para vehículos multirotor, aplicando y desarrollando diversas técnicas de control y de machine learning con resultados innovadores. El objetivo principal de la tesis es obtener un sistema de GNC capaz de dirigir el vehículo para que siga una trayectoria predefinida mientras evita los obstáculos que puedan aparecer en el recorrido del vehículo. El sistema debe ser adaptable a diferentes trayectorias, situaciones y misiones, reduciendo el esfuerzo realizado en el ajuste y la parametrización de los métodos propuestos. La plataforma experimental, formada por el cuadricoptero Asctec Hummingbird, se estudia y describe en detalle. Se obtiene un modelo matemático completo de la plataforma y se desarrolla una herramienta de simulación, la cual es de código libre. Además, se diseña un controlador autopilot, el cual es implementado en la plataforma real. La parte de control está enfocada en el problema de path following. En este problema, el vehículo debe seguir una trayectoria predefinida en el espacio tridimensional sin ninguna restricción temporal Se estudian, implementan y comparan varios algoritmos de control y geométricos de path following. Luego, se mejoran los algoritmos geométricos usando redes neuronales para convertirlos en algoritmos adaptativos. Para finalizar, se desarrolla un método de path following basado en técnicas de aprendizaje por refuerzo profundo (deep reinforcement learning). Este método implementa el algoritmo Deep Deterministic Policy Gradient. El agente inteligente resultante es entrenado en un simulador realista de multirotores y validado en la plataforma experimental real con éxito. Los resultados muestran que el agente es capaz de seguir de forma precisa la trayectoria de referencia adaptando la velocidad del vehículo según la curvatura del recorrido. En la parte de navegación se implementa un sistema de detección de obstáculos basado en el uso de un sensor LIDAR. Se deriva un modelo del sensor y este se incluye en el simulador. Además, se desarrolla un método para tratar las medidas del sensor para eliminar las posibles detecciones del suelo. En cuanto a la parte de guiado, está focalizada en el problema de reactive path planning. Es decir, un algoritmo de planificación de trayectoria que es capaz de re-planear el recorrido del vehículo al instante si ocurre algún evento inesperado, como lo es la detección de un obstáculo en el recorrido del vehículo. Se desarrolla un método basado en aprendizaje por refuerzo profundo para la evasión de obstáculos. Este implementa el algoritmo Deep Deterministic Policy Gradient. El agente de aprendizaje por refuerzo se entrena y valida en un simulador de multirotors realista. Este agente se combina con el agente de path following y el resto de elementos desarrollados en la tesis para obtener un sistema GNC capaz de seguir diferentes tipos de trayectorias evadiendo los obstáculos que estén en el recorrido del vehículo.
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Alsaif, Saif A. "Echoic Flow for Guidance and Control." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1543864969419357.

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Wright, David Andrew. "Guidance and control of sounding rockets." Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/5077.

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This dissertation presents the design, fabrication and testing of a sounding rocket flight computer for the South African Astronomical Observatory (SAAO). Sounding rockets carry instruments with which to take measurements in the Earth’s atmosphere in sub-orbital flight. The South African Astronomical Observatory (SAAO) requires a flight computer for their sounding rockets. This flight computer is to replace the current commercial flight computer currently in use improving on its functionality and expandability.
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Hallberg, Eric N. "On integrated plant, control and guidance design." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1997. http://handle.dtic.mil/100.2/ADA341957.

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Dissertation (Ph.D. in Aeronautics and Astronautics) Naval Postgraduate School, September 1997.
"September 1997." Dissertation supervisor(s): Isaac I. Kaminer. Includes bibliographical references (p. 187-190). Also available online.
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Dellicker, Scott Henry. "Low cost parachute guidance, navigation, and control." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA369203.

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Thesis (M.S. in Aeronautical Engineering) Naval Postgraduate School, September 1999.
"September 1999". Thesis advisor(s): Richard M. Howard, Isaac I. Kaminer. Includes bibliographical references (p. 91-92). Also available online.
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Simakis, Dimitrios A. "Vehicle guidance and control along circular trajectories." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/24101.

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McConnell, George. "Digital bank-to-turn control and guidance." Thesis, Queen's University Belfast, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303013.

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Books on the topic "Guidance and control"

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Canadian Institute of Chartered Accountants. and Canadian Institute of Chartered Accountants. Criteria of Control Board., eds. Guidance on control. Toronto: Canadian Institute of Chartered Accountants, 1995.

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North Atlantic Treaty Organization. Advisory Group for Aerospace Research and Development. Software for guidance and control. Neuilly sur Seine, France: AGARD, 1991.

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Great Britain. Department of the Environment. Planning policy guidance: Structure plans and regional planning guidance. London: DoE, 1989.

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Great Britain. Department of the Environment. Planning policy guidance. London: HMSO, 1988.

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Great Britain. Department of the Environment. Planning policy guidance: Housing. London: DoE, 1989.

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Williams, J. Management accounting control systems: Guidance & revision. 4th ed. London: CIMA, 1997.

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Yan, Liang, Haibin Duan, and Xiang Yu, eds. Advances in Guidance, Navigation and Control. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-15-8155-7.

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Mazzini, Leonardo. Flexible Spacecraft Dynamics, Control and Guidance. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-25540-8.

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Rayfield, Janine. Infection control guidance for general practice. [Bathgate?]: INCA, 2003.

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Yan, Liang, Haibin Duan, and Yimin Deng, eds. Advances in Guidance, Navigation and Control. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6613-2.

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Book chapters on the topic "Guidance and control"

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Yakimenko, Oleg, and Thomas Jann. "Guidance, Navigation, and Control." In Precision Aerial Delivery Systems: Modeling, Dynamics, and Control, 391–527. Reston, VA: American Institute of Aeronautics and Astronautics, Inc., 2015. http://dx.doi.org/10.2514/5.9781624101960.0391.0528.

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Hull, David G. "Fixed Final Time Guidance." In Optimal Control Theory for Applications, 199–220. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-1-4757-4180-3_12.

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Mazzini, Leonardo. "Orbital Dynamics and Guidance." In Flexible Spacecraft Dynamics, Control and Guidance, 209–60. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25540-8_7.

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Mazzini, Leonardo. "Attitude Control Methods." In Flexible Spacecraft Dynamics, Control and Guidance, 181–208. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25540-8_6.

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Flemisch, Frank, Hermann Winner, Ralph Bruder, and Klaus Bengler. "Cooperative Guidance, Control, and Automation." In Handbook of Driver Assistance Systems, 1471–81. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12352-3_58.

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Flemisch, Frank, Hermann Winner, Ralph Bruder, and Klaus Bengler. "Cooperative guidance, control and automation." In Handbook of Driver Assistance Systems, 1–9. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-09840-1_58-1.

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Sun, Zezhou. "Guidance, Navigation and Control Technology." In Space Science and Technologies, 189–234. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4794-2_6.

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Suresh, B. N., and K. Sivan. "Navigation Guidance and Control System." In Integrated Design for Space Transportation System, 581–661. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2532-4_14.

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Longacre, Kenneth, John Osborn-Hoff, and Aaron Brown. "Guidance, Navigation, Control and Propulsion." In Human Spaceflight Operations: Lessons Learned from 60 Years in Space, 277–334. Reston, VA: American Institute of Aeronautics and Astronautics, Inc., 2021. http://dx.doi.org/10.2514/5.9781624104770.0277.0334.

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Soitinaho, Riikka, and Timo Oksanen. "Guidance, Auto-Steering Systems and Control." In Agriculture Automation and Control, 239–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70400-1_10.

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Conference papers on the topic "Guidance and control"

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Shah, M. Zamurad, M. Kemal Ozgoren, and Raza Samar. "Sliding mode based longitudinal guidance of UAVs." In 2014 UKACC International Conference on Control (CONTROL). IEEE, 2014. http://dx.doi.org/10.1109/control.2014.6915126.

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Guo, Yanning, Yao Zhang, Guangfu Ma, and Tianyi Zeng. "Multi-power sliding mode guidance for Mars powered descent phase." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737537.

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Ross, I. Michael, Ronald J. Proulx, and Mark Karpenko. "Unscented guidance." In 2015 American Control Conference (ACC). IEEE, 2015. http://dx.doi.org/10.1109/acc.2015.7172217.

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Williams, D. E., B. Friedland, and J. Richman. "Integrated Guidance and Control for Combined Command/Homing Guidance." In 1988 American Control Conference. IEEE, 1988. http://dx.doi.org/10.23919/acc.1988.4789781.

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Merlinge, Nicolas, Nadjim Horri, Karim Dahia, Helene Piet-Lahanier, and James Brusey. "Box Particle Control for Aerospace Vehicles Guidance Under Failure Probability Constraints." In 2018 UKACC 12th International Conference on Control (CONTROL). IEEE, 2018. http://dx.doi.org/10.1109/control.2018.8516773.

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LAWRENCE, R. "Advanced missile guidance." In Navigation and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-2726.

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Hanson, John, M. Shrader, and Craig Cruzen. "Ascent guidance comparisons." In Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-3568.

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Shinar, J., I. Forte, and B. Kantor. "Mixed Strategy Guidance (MSG): A New High Performance Missile Guidance Law." In 1992 American Control Conference. IEEE, 1992. http://dx.doi.org/10.23919/acc.1992.4792369.

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Lu, Ping, Christopher J. Cerimele, Michael A. Tigges, and Daniel A. Matz. "Optimal Aerocapture Guidance." In AIAA Guidance, Navigation, and Control Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2015. http://dx.doi.org/10.2514/6.2015-1771.

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Xu, Qiangqiang, Jianquan Ge, and Tao Yang. "Multiple Missiles Cooperative Guidance Based on Proportional Navigation Guidance." In 2020 Chinese Control And Decision Conference (CCDC). IEEE, 2020. http://dx.doi.org/10.1109/ccdc49329.2020.9164151.

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Reports on the topic "Guidance and control"

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Freitag, Lee E. Acoustic Communication for High-Doppler Guidance and Control. Fort Belvoir, VA: Defense Technical Information Center, July 2002. http://dx.doi.org/10.21236/ada404027.

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Alford, Cecil O., J. I. Chamdani, T. C. Huang, T. Kubota, and F. Ghannadian. Guidance, Navigation and Control Digital Emulation Technology Laboratory. Fort Belvoir, VA: Defense Technical Information Center, September 1994. http://dx.doi.org/10.21236/ada284339.

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Speyer, Jason L. A Disturbance Attenuation Approach to Missile Guidance and Control. Fort Belvoir, VA: Defense Technical Information Center, March 1997. http://dx.doi.org/10.21236/ada329598.

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Bradbury, Karmin, Amy Bouska, Carmen Carruthers, and April Sperstad. Guidance Regarding Flow Control : An Evaluation of Midwestern Practices. University of Iowa, May 2001. http://dx.doi.org/10.17077/sa3o-1kov.

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Menon, P. K., and Ernest J. Ohlmeyer. Integrated Guidance-Control Systems for Fixed-Aim Warhead Missiles. Fort Belvoir, VA: Defense Technical Information Center, November 2000. http://dx.doi.org/10.21236/ada389283.

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Fresconi, Frank, Ilmars Celmins, and Sidra I. Silton. Theory, Guidance, and Flight Control for High Maneuverability Projectiles. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada593328.

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Fresconi, Frank, and Jon Rogers. Guidance and Control of a Man-Portable Precision Munition Concept. Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada606639.

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Mahan, Robert E., Jerry D. Fluckiger, Samuel L. Clements, Cody W. Tews, John R. Burnette, Craig A. Goranson, and Harold Kirkham. Secure Data Transfer Guidance for Industrial Control and SCADA Systems. Office of Scientific and Technical Information (OSTI), September 2011. http://dx.doi.org/10.2172/1030885.

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Stilwell, Daniel J., and Bradley E. Bishop. Decentralized Guidance, Navigation, and Control for Platoons of Cooperating UUVs. Fort Belvoir, VA: Defense Technical Information Center, August 2001. http://dx.doi.org/10.21236/ada625233.

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Bishop, Bradley E. Decentralized Guidance, Navigation, and Control for Platoons of Cooperating UUVs. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada627048.

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