Relevant bibliographies by topics / Linear Quadratic Regulator

Academic literature on the topic 'Linear Quadratic Regulator'

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Published: 4 June 2021
Last updated: 3 March 2023

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Journal articles on the topic "Linear Quadratic Regulator"

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Alexandrova, Mariela, Nasko Atanasov, Ivan Grigorov, and Ivelina Zlateva. "Linear Quadratic Regulator Procedure and Symmetric Root Locus Relationship Analysis." International Journal of Engineering Research and Science 3, no. 11 (November 30, 2017): 27–33. http://dx.doi.org/10.25125/engineering-journal-ijoer-nov-2017-7.

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Khlebnikov, M. V., and P. S. Shcherbakov. "Linear Quadratic Regulator: II. Robust Formulations." Automation and Remote Control 80, no. 10 (October 2019): 1847–60. http://dx.doi.org/10.1134/s0005117919100060.

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Vissio, Giacomo, Duarte Valério, Giovanni Bracco, Pedro Beirão, Nicola Pozzi, and Giuliana Mattiazzo. "ISWEC linear quadratic regulator oscillating control." Renewable Energy 103 (April 2017): 372–82. http://dx.doi.org/10.1016/j.renene.2016.11.046.

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Ochi, Y., and K. Kanai. "Eigenstructure Assignment for Linear Quadratic Regulator." IFAC Proceedings Volumes 29, no. 1 (June 1996): 1098–103. http://dx.doi.org/10.1016/s1474-6670(17)57811-8.

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Danas, Aidil, Heru Dibyo Laksono, and Syafii . "Perbaikan Kestabilan Dinamik Sistem Tenaga Listrik Multimesin dengan Metoda Linear Quadratic Regulator." Jurnal Nasional Teknik Elektro 2, no. 2 (September 1, 2013): 72–78. http://dx.doi.org/10.20449/jnte.v2i2.88.

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Wu, Guangyu, Lu Xiong, Gang Wang, and Jian Sun. "Linear Quadratic Regulator of Discrete-Time Switched Linear Systems." IEEE Transactions on Circuits and Systems II: Express Briefs 67, no. 12 (December 2020): 3113–17. http://dx.doi.org/10.1109/tcsii.2020.2973302.

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NAKAJIMA, Kyohei, Koichi KOBAYASHI, and Yuh YAMASHITA. "Linear Quadratic Regulator with Decentralized Event-Triggering." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E100.A, no. 2 (2017): 414–20. http://dx.doi.org/10.1587/transfun.e100.a.414.

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I. Abdulla, Abdulla. "Linear Quadratic Regulator Using Artificial Immunize System." AL-Rafdain Engineering Journal (AREJ) 20, no. 3 (June 28, 2012): 80–91. http://dx.doi.org/10.33899/rengj.2012.50481.

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Abdelrahman, M., G. Aryassov, M. Tamre, and I. Penkov. "System Vibration Control Using Linear Quadratic Regulator." International Journal of Applied Mechanics and Engineering 27, no. 3 (August 29, 2022): 1–8. http://dx.doi.org/10.2478/ijame-2022-0031.

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Abstract Balancing a bipedal robot movement against external perturbations is considered a challenging and complex topic. This paper discusses how the vibration caused by external disturbance has been tackled by a Linear Quadratic Regulator, which aims to provide optimal control to the system. A simulation was conducted on MATLAB in order to prove the concept. Results have shown that the linear quadratic regulator was successful in stabilizing the system efficiently.
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Gavina, A., J. Matos, and P. B. Vasconcelos. "Tau Method for Linear Quadratic Regulator Problems." Journal of Applied Nonlinear Dynamics 3, no. 2 (June 2014): 139–46. http://dx.doi.org/10.5890/jand.2014.06.004.

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Dissertations / Theses on the topic "Linear Quadratic Regulator"

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Mouadeb, Abdu-Nasser R. "Extension of linear quadratic regulator theory and its applications." Thesis, University of Ottawa (Canada), 1992. http://hdl.handle.net/10393/7535.

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Linear Quadratic Regulatory theory (L.Q.R.) has received widespread application due to its simplicity and also due to the fact that the control provided this by theory is linear in form. These features make the implication of feedback control and easy task. In contrast, nonlinear regulation lack those attractive features enjoyed by the linear regulator. Moreover, in order to obtain the feedback control, one has to solve Hamilton-Jacobi-Bellman equation which is not an easy task. Also, if solution can be obtained, implementation is not always practical. In this work, we extend the Linear Quadratic Regulatory theory to the following; (I) LQR theory is modified for the case when there is no control contribution to the cost functional. (II) LQR is used to regulate or fine-tune a nonlinear system around a nominal trajectory through linearization of nonlinear systems. (III) Applying the LQR theory for the regulation of angular velocities of a three-axes satellite around a nominal point. (IV) Applying the LQR for the regulation of the movement of a robot around a time-optional trajectory. (V) The limitation of the control obtained through linearization is indicated.
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Benner, Peter, and Jens Saak. "Linear-Quadratic Regulator Design for Optimal Cooling of Steel Profiles." Universitätsbibliothek Chemnitz, 2006. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200601597.

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We present a linear-quadratic regulator (LQR) design for a heat transfer model describing the cooling process of steel profiles in a rolling mill. Primarily we consider a feedback control approach for a linearization of the nonlinear model given there, but we will also present first ideas how to use local (in time) linearizations to treat the nonlinear equation with a regulator approach. Numerical results based on a spatial finite element discretization and a numerical algorithm for solving large-scale algebraic Riccati equations are presented both for the linear and nonlinear models.
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Khalid, Muhammad Salman. "Linear Quadratic Regulator and Receding Horizon Control for Constrained Systems." Thesis, University of Sheffield, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515489.

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Aravinthan, Abhiramy. "Linear quadratic regulator design for doubly fed induction generator using singular perturbation techniques." Thesis, Wichita State University, 2012. http://hdl.handle.net/10057/5523.

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Doubly fed induction generators (DFIG) are widely used in wind power generation because of their ability to be operated at varying rotational speeds while producing power output at a constant frequency. Electrical dynamics of a DFIG is modeled using field oriented control and represented as fourth order system. This fourth order dynamics exposes a two-time scale behavior. Using singular perturbation techniques the time scales can be separated as slow and fast subsystems. Feedback control schemes can be designed and the closed-loop stability of each model can be compared. In this work, a linear quadratic feedback controller is designed for the DFIG electrical dynamics using exact, reduced order and composite models. The performances of the closed loop models are compared based on the system cost. The robustness and reliability of the control schemes are analyzed for each controller designs based on the nominal system. Based on the analysis and results, the reduced order controller performance is equally as good as the exact and composite designs during steady state operations.
Thesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science
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Nelson, Karen E. (Karen Elizabeth) M. Eng Massachusetts Institute of Technology. "Active control of tensegrity structures and its applications using Linear Quadratic Regulator algorithms." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66845.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 61-62).
The concept of responsive architecture has inspired the idea structures which are adaptable and change in order to better fit the user. This idea can be extended to structural engineering with the implementing of structures which change to better take on their external loading. The following text explores the utilization of active control for tensegrity systems in order to achieve an adaptable structure. To start, a background of the physical characteristics of these structures is given along with the methods which are used to find their form. Next, the different methods which have been previously used to achieve active control in tensegrity are reviewed as well as the objectives they intended to achieve. From there, the Linear Quadratic Regulator (LQR) algorithm is introduced as a possible method to be used in designing active control. A planar tensegrity beam is described, whose form was found by the force density method. A simulation is then conducted, which applies the LQR algorithm to this structure for the purposes of active control. This simulation served both to demonstrate the force density and LQR methods, as well as to study how different control parameters and actuator placements effects the efficiency of the control. This text concludes with a discussion of the results of this simulation.
by Karen E. Nelson.
M.Eng.
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Uddin, Md Mosleh. "Active Vibration Control of Helicopter Rotor Blade by Using a Linear Quadratic Regulator." ScholarWorks@UNO, 2018. https://scholarworks.uno.edu/td/2499.

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Active vibration control is a widely implemented method for the helicopter vibration control. Due to the significant progress in microelectronics, this technique outperforms the traditional passive control technique due to weight penalty and lack of adaptability for the changing flight conditions. In this thesis, an optimal controller is designed to attenuate the rotor blade vibration. The mathematical model of the triply coupled vibration of the rotating cantilever beam is used to develop the state-space model of an isolated rotor blade. The required natural frequencies are determined by the modified Galerkin method and only the principal aerodynamic forces acting on the structure are considered to obtain the elements of the input matrix. A linear quadratic regulator is designed to achieve the vibration reduction at the optimum level and the controller is tuned for the hovering and forward flight with different advance ratios.
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Bushong, Philip Merton. "A multi-loop guidance scheme using singular perturbation and linear quadratic regulator techniques simultaneously." Diss., This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-07282008-135643/.

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Vugrin, Eric D. "On Approximation and Optimal Control of Nonnormal Distributed Parameter Systems." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/11149.

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For more than 100 years, the Navier-Stokes equations and various linearizations have been used as a model to study fluid dynamics. Recently, attention has been directed toward studying the nonnormality of linearized problems and developing convergent numerical schemes for simulation of these sytems. Numerical schemes for optimal control problems often require additional properties that may not be necessary for simulation; these properties can be critical when studying nonnormal problems. This research is concerned with approximating infinite dimensional optimal control problems with nonnormal system operators. We examine three different finite element methods for a specific convection-diffusion equation and prove convergence of the infinitesimal generators. Additionally, for two of these schemes, we prove convergence of the associated feedback gains. We apply these three schemes to control problems and compare the performance of all three methods.
Ph. D.
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Bagheri, Shahriar. "Modeling, Simulation and Control System Design for Civil Unmanned Aerial Vehicle (UAV)." Thesis, Umeå universitet, Institutionen för tillämpad fysik och elektronik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-96458.

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Unmanned aerial systems have been widely used for variety of civilian applications over the past few years. Some of these applications require accurate guidance and control. Consequently, Unmanned Aerial Vehicle (UAV) guidance and control attracted many researchers in both control theory and aerospace engineering. Flying wings, as a particular type of UAV, are considered to have one of the most efficient aerodynamic structures. It is however difficult to design robust controller for such systems. This is due to the fact that flying wings are highly sensitive to control inputs. The focus of this thesis is on modeling and control design for a UAV system. The platform understudy is a flying wing developed by SmartPlanes Co. located in Skellefteå, Sweden. This UAV is particularly used for topological mapping and aerial photography. The novel approach suggested in this thesis is to use two controllers in sequence. More precisely, Linear Quadratic Regulator (LQR) is suggested to provide robust stability, and Proportional, Integral, Derivative (PID) controller is suggested to provide reference signal regulation. The idea behind this approach is that with LQR in the loop, the system becomes more stable and less sensitive to control signals. Thus, PID controller has an easier task to do, and is only used to provide the required transient response. The closed-loop system containing the developed controller and a UAV non-linear dynamic model was simulated in Simulink. Simulated controller was then tested for stability and robustness with respect to some parametric uncertainty. Obtained results revealed that the LQR successfully managed to provide robust stability, and PID provided reference signal regulation.
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Alvarez, Genesis Barbie. "Control Design for a Microgrid in Normal and Resiliency Modes of a Distribution System." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/94627.

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As inverter-based distributed energy resources (DERs) such as photovoltaic (PV) and battery energy storage system (BESS) penetrate within the distribution system. New challenges regarding how to utilize these devices to improve power quality arises. Before, PV systems were required to disconnect from the grid during a large disturbance, but now smart inverters are required to have dynamically controlled functions that allows them to remain connected to the grid. Monitoring power flow at the point of common coupling is one of the many functions the controller should perform. Smart inverters can inject active power to pick up critical load or inject reactive power to regulate voltage within the electric grid. In this context, this thesis focuses on a high level and local control design that incorporates DERs. Different controllers are implemented to stabilize the microgrid in an Islanding and resiliency mode. The microgrid can be used as a resiliency source when the distribution is unavailable. An average model in the D-Q frame is calculated to analyze the inherent dynamics of the current controller for the point of common coupling (PCC). The space vector approach is applied to design the voltage and frequency controller. Secondly, using inverters for Volt/VAR control (VVC) can provide a faster response for voltage regulation than traditional voltage regulation devices. Another objective of this research is to demonstrate how smart inverters and capacitor banks in the system can be used to eliminate the voltage deviation. A mixed-integer quadratic problem (MIQP) is formulated to determine the amount of reactive power that should be injected or absorbed at the appropriate nodes by inverter. The Big M method is used to address the nonconvex problem. This contribution can be used by distribution operators to minimize the voltage deviation in the system.
Master of Science
Reliable power supply from the electric grid is an essential part of modern life. This critical infrastructure can be vulnerable to cascading failures or natural disasters. A solution to improve power systems resilience can be through microgrids. A microgrid is a small network of interconnected loads and distributed energy resources (DERs) such as microturbines, wind power, solar power, or traditional internal combustion engines. A microgrid can operate being connected or disconnected from the grid. This research emphases on the potentially use of a Microgrid as a resiliency source during grid restoration to pick up critical load. In this research, controllers are designed to pick up critical loads (i.e hospitals, street lights and military bases) from the distribution system in case the electric grid is unavailable. This case study includes the design of a Microgrid and it is being tested for its feasibility in an actual integration with the electric grid. Once the grid is restored the synchronization between the microgrid and electric must be conducted. Synchronization is a crucial task. An abnormal synchronization can cause a disturbance in the system, damage equipment, and overall lead to additional system outages. This thesis develops various controllers to conduct proper synchronization. Interconnecting inverter-based distributed energy resources (DERs) such as photovoltaic and battery storage within the distribution system can use the electronic devices to improve power quality. This research focuses on using these devices to improve the voltage profile within the distribution system and the frequency within the Microgrid.
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Books on the topic "Linear Quadratic Regulator"

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1964-, Hartley T. T., and Chicatelli S. P. 1964-, eds. The hyperbolic map and applications to the linear quadratic regulator. New York: Springer-Verlag, 1989.

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Daiuto, Brian J., Tom T. Hartley, and Stephen P. Chicatelli, eds. The Hyperbolic Map and Applications to the Linear Quadratic Regulator. Berlin/Heidelberg: Springer-Verlag, 1989. http://dx.doi.org/10.1007/bfb0042968.

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Daiuto, Brian J. The Hyperbolic Map and Applications to the Linear Quadratic Regulator. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989.

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Rosen, I. G. Optimal discrete-time LQR problems for parabolic systems with unbounded input - approximation and convergence. Hampton, Va: ICASE, 1988.

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Rosen, I. G. On the continuous dependence with respect to sampling of the linear quadratic regulator problem for distributed parameter systems. Hampton, Va: Institute for Computer Applications in Science and Engineering, 1990.

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Jones, Mark T. A language comparison for scientific computing on MIMD architectures. Hampton, Va: ICASE, 1989.

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Marc, Buchner, and United States. National Aeronautics and Space Administration., eds. A parametric LQ approach to multiobjective control system design. [Washington, DC]: NASA, 1988.

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Gibson, J. S. Numerical approximation for the infinite-dimensional discrete-time optimal linear-quadratic regulator problem. Hampton, Va: ICASE, 1986.

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Banks, H. Thomas. A numerical algorithm for optimal feedback gains in high dimensional LQR problems. Hampton, Va: ICASE, 1986.

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Gibson, J. S. Shifting the closed-loop spectrum in the optimal linear quadratic regulator problem for hereditary systems. Hampton, Va: ICASE, 1986.

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Book chapters on the topic "Linear Quadratic Regulator"

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Björk, Tomas, Mariana Khapko, and Agatha Murgoci. "The Linear Quadratic Regulator." In Springer Finance, 23–25. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81843-2_3.

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Hajiyev, Chingiz, Halil Ersin Soken, and Sıtkı Yenal Vural. "Linear Quadratic Regulator Controller Design." In State Estimation and Control for Low-cost Unmanned Aerial Vehicles, 171–200. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16417-5_10.

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Mohammadi, Hesameddin, Mahdi Soltanolkotabi, and Mihailo R. Jovanović. "Model-Free Linear Quadratic Regulator." In Handbook of Reinforcement Learning and Control, 173–85. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-60990-0_6.

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Björk, Tomas, Mariana Khapko, and Agatha Murgoci. "The Inconsistent Linear Quadratic Regulator." In Springer Finance, 195–98. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81843-2_19.

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Björk, Tomas, Mariana Khapko, and Agatha Murgoci. "The Continuous-Time Linear Quadratic Regulator." In Springer Finance, 129–32. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81843-2_12.

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Delchamps, David F. "The Discrete-Time Linear Quadratic Regulator Problem." In State Space and Input-Output Linear Systems, 393–405. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-3816-4_27.

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Delchamps, David F. "The Continuous-Time Linear Quadratic Regulator Problem." In State Space and Input-Output Linear Systems, 406–15. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-3816-4_28.

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Munje, Ravindra, Balasaheb Patre, and Akhilanand Tiwari. "State Feedback Control Using Linear Quadratic Regulator." In Energy Systems in Electrical Engineering, 61–77. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3014-7_4.

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Lavretsky, Eugene, and Kevin A. Wise. "Optimal Control and the Linear Quadratic Regulator." In Robust and Adaptive Control, 27–50. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4396-3_2.

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Rizvi, Syed Ali Asad, and Zongli Lin. "Model-Free Design of Linear Quadratic Regulator." In Output Feedback Reinforcement Learning Control for Linear Systems, 27–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15858-2_2.

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Conference papers on the topic "Linear Quadratic Regulator"

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Carlos, Hugo, Jean-Bernard Hayer, and Rafael Murrieta-Cid. "Regression-Based Linear Quadratic Regulator." In 2018 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. http://dx.doi.org/10.1109/icra.2018.8460479.

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Li, Yan, and YangQuan Chen. "Fractional Order Linear Quadratic Regulator." In 2008 IEEE/ASME International Conference on Mechtronic and Embedded Systems and Applications (MESA). IEEE, 2008. http://dx.doi.org/10.1109/mesa.2008.4735696.

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Ludeke, D. Taylor, and Tetsuya Iwasaki. "Linear Quadratic Regulator for Autonomous Oscillation." In 2019 American Control Conference (ACC). IEEE, 2019. http://dx.doi.org/10.23919/acc.2019.8815208.

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Hole, K. E. "Design of Robust Linear Quadratic Regulator." In 1989 American Control Conference. IEEE, 1989. http://dx.doi.org/10.23919/acc.1989.4790323.

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Tzortzis, Ioannis, Charalambos D. Charalambous, Themistoklis Charalambous, Christos K. Kourtellaris, and Christoforos N. Hadjicostis. "Robust Linear Quadratic Regulator for uncertain systems." In 2016 IEEE 55th Conference on Decision and Control (CDC). IEEE, 2016. http://dx.doi.org/10.1109/cdc.2016.7798481.

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Jongeneel, Wouter, Tyler Summers, and Peyman Mohajerin Esfahani. "Robust Linear Quadratic Regulator: Exact Tractable Reformulation." In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9028884.

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Nakajima, Kyohei, Koichi Kobayashi, and Yuh Yamashita. "Linear quadratic regulator with decentralized event-triggering." In IECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2016. http://dx.doi.org/10.1109/iecon.2016.7793650.

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Gromaszek, Konrad, Beata Kuśmierz, and Krzysztof Kryk. "Inverted pendulum model Linear–Quadratic Regulator (LQR)." In Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2018, edited by Ryszard S. Romaniuk and Maciej Linczuk. SPIE, 2018. http://dx.doi.org/10.1117/12.2501686.

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Heemels, W. P. M. H., S. J. L. van Eijndhoven, and A. A. Stoorvogel. "Linear quadratic regulator problem with positive controls." In 1997 European Control Conference (ECC). IEEE, 1997. http://dx.doi.org/10.23919/ecc.1997.7082364.

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Schildbach, Georg, Paul Goulart, and Manfred Morari. "The Linear Quadratic Regulator with chance constraints." In 2013 European Control Conference (ECC). IEEE, 2013. http://dx.doi.org/10.23919/ecc.2013.6669660.

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