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Journal articles on the topic 'Linear Quadratic Regulator'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

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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2

CS, Vishnu, and Riya Mary Francis. "Speed Control of BLDC Motor by Using Tuned Linear Quadratic Regulator." International Journal of Scientific Engineering and Research 3, no. 8 (August 27, 2015): 36–40. https://doi.org/10.70729/ijser15383.

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3

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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4

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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5

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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6

Sairoel, Amertet Finecomes, L. Gebre Fisseha, M. Mesene Abush, and Abebaw Solomon. "Optimization of automobile active suspension system using minimal order." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (June 1, 2022): 2378–92. https://doi.org/10.11591/ijece.v12i3.pp2378-2392.

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This paper presents an analysis and design of linear quadratic regulator for reduced order full car suspension model incorporating the dynamics of the actuator to improve system performance, aims at benefiting: Ride comfort, long life of vehicle, and stability of vehicle. Vehicle’s road holding or handling and braking for good active safety and driving pleasure and keeping vehicle occupants comfortable and reasonably well isolated from road noise, bumps, and vibrations are become a key research area conducted by many researchers around the globe. Different researchers were tested effectiveness of different controllers for different vehicle model without considering the actuator dynamics. In this paper full vehicle model was reduced to a minimal order using minimal realization technique. The entire system responses were simulated in MATLAB/Simulink environment. The effectiveness of linear quadratic regulator controller was compared for the system model with and without actuator dynamics for different road profiles. The simulation results were indicated that percentage reduction in the peak value of vertical and horizontal velocity for the linear quadratic regulator with actuator dynamics relative to linear quadratic regulator without actuator dynamics was 28.57%. Overall simulation results were demonstrated that proposed control scheme has able to improve the effectiveness of the car model for both ride comfort and stability.

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7

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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8

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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9

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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10

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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11

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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12

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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13

Khlebnikov, M. V., P. S. Shcherbakov, and V. N. Chestnov. "Linear-quadratic regulator. I. a new solution." Automation and Remote Control 76, no. 12 (December 2015): 2143–55. http://dx.doi.org/10.1134/s0005117915120048.

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14

Heemels, W. P. M. H., S. J. L. Van Eijndhoven, and A. A. Stoorvogel. "Linear quadratic regulator problem with positive controls." International Journal of Control 70, no. 4 (January 1998): 551–78. http://dx.doi.org/10.1080/002071798222208.

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15

Feng, Lechen, and Yuan-Hua Ni. "Accelerated optimization landscape of linear–quadratic regulator." Automatica 171 (January 2025): 111927. http://dx.doi.org/10.1016/j.automatica.2024.111927.

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16

Wu, Guangyu, Jian Sun, and Jie Chen. "Optimal Linear Quadratic Regulator of Switched Systems." IEEE Transactions on Automatic Control 64, no. 7 (July 2019): 2898–904. http://dx.doi.org/10.1109/tac.2018.2872204.

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17

Escárate, Pedro, Juan C. Agüero, Sebastián Zúñiga, Mario Castro, and Javier Garcés. "Linear quadratic regulator for laser beam shaping." Optics and Lasers in Engineering 94 (July 2017): 90–96. http://dx.doi.org/10.1016/j.optlaseng.2017.02.009.

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18

Kamel, Ahmed, Ramin Esmzad, Nariman Niknejad, and Hamidreza Modares. "Robust adaptive maximum-entropy linear quadratic regulator." IFAC Journal of Systems and Control 32 (June 2025): 100305. https://doi.org/10.1016/j.ifacsc.2025.100305.

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19

Mohammad, A. Thanoon, R. Awad Sohaib, and Kh. Abdullah Ismael. "LQR controller design for stabilization of non-linear DIP system based on ABC algorithm." Eastern-European Journal of Enterprise Technologies 2, no. 2(122) (April 30, 2023): 36–44. https://doi.org/10.15587/1729-4061.2023.275657.

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Inverted pendulum systems, such as double or single, rotational or translational inverted pendulums are non-linear and unstable, which have been the most dominant approaches for control systems. The double inverted pendulum is one kind of a non-linear, unstable system, multivariable, and strong coupling with a wide range of control methods. To model these types of systems, many techniques have been proposed so that motivating researchers to come up with new innovative solutions. The Linear Quadratic Regulator (LQR) controller has been a common controller used in this field. Meanwhile, the Artificial Bee Colony (ABC) technique has become an alternative solution for employing Bee Swarm Intelligence algorithms. The research solutions of the artificial bee colony algorithm in the literature can be beneficial, however, the utilization of discovered sources of food is ineffective. Thus, in this paper, we aim to provide a double inverted pendulum system for stabilization by selecting linear quadratic regulator parameters using a bio-inspired optimization methodology of artificial bee colony and weight matrices Q and R. The results show that when the artificial bee colony algorithm is applied to a linear quadratic regulator controller, it gains the capacity to autonomously tune itself in an online process. To further demonstrate the efficiency and viability of the suggested methodology, simulations have been performed and compared to conventional linear quadratic regulator controllers. The obtained results demonstrate that employing artificial intelligence (AI) together with the proposed controller outperforms the conventional linear quadratic regulator controllers by more than 50 % in transient response and improved time response and stability performance

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20

Vo, Minh-Tai, Van-Dong-Hai Nguyen, Hoai-Nghia Duong, and Vinh-Hao Nguyen. "Combining Passivity-Based Control and Linear Quadratic Regulator to Control a Rotary Inverted Pendulum." Journal of Robotics and Control (JRC) 4, no. 4 (July 21, 2023): 479–90. http://dx.doi.org/10.18196/jrc.v4i4.18498.

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In this manuscript, new combination methodology is proposed, which named combining Passivity-Based Control and Linear Quadratic Regulator (for short, CPBC-LQR), to support the stabilization process as the system is far from equilibrium point. More precisely, Linear Quadratic Regulator (for short, LQR) is used together with Passivity-Based Control (for short, PBC) controller. Though passivity-based control and linear quadratic regulator are two control methods, it is possible to integrate them together. The combination of passivity-based control and linear quadratic regulator is analyzed, designed and implemented on so-called rotary inverted pendulum system (for short, RIP). In this work, CPBC-LQR is validated and discussed on both MATLAB/Simulink environment and real-time experimental setup. The numerical simulation and experimental results reveal the ability of CPBC-LQR control scheme in stabilization problem and achieve a good and stable performance. Effectiveness and feasibility of proposed controller are confirmed via comparative simulation and experiments.

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21

Jara Huanca, Fidel, Obidio Rubio Mercedes, and Julio Ruiz Claeyssen. "Fundamental response in the vibration control of buildings subject to seismic excitation with ATMD." Selecciones Matemáticas 10, no. 01 (July 26, 2023): 147–57. http://dx.doi.org/10.17268/sel.mat.2023.01.13.

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The linear quadratic regulator for vibration systems subject to seismic excitations is discussed in his own physical newtonian space as a second-order linear differential system with matrix coefficients. The linear quadratic regulator leads to a fourth-order system and second-order transversality conditions. Those systems are studied with a matrix basis generated by a fundamental matrix solution.

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22

Abdul samad, Bdereddin, Mahmoud Mohamed, Fatih Anayi, and Yevgen Melikhov. "An Investigation of Various Controller Designs for Multi-Link Robotic System (Robogymnast)." Knowledge 2, no. 3 (September 6, 2022): 465–86. http://dx.doi.org/10.3390/knowledge2030028.

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An approach to controlling the three-link Robogymnast robotic gymnast and assessing stability is proposed and examined. In the study, a conventionally configured linear quadratic regulator is applied and compared with a fuzzy logic linear quadratic regulator hybrid approach for stabilising the Robogymnast. The Robogymnast is designed to replicate the movement of a human as they hang with both hands holding the high bar and then work to wing up into a handstand, still gripping the bar. The system, therefore has a securely attached link between the hand element and the ‘high bar’, which is mounted on ball bearings and can rotate freely. Moreover, in the study, a mathematical model for the system is linearised, investigating the means of determining the state space in the system by applying Lagrange’s equation. The fuzzy logic linear quadratic regulator controller is used to identify how far the system responses stabilise when it is implemented. This paper investigates factors affecting the control of swing-up in the underactuated three-link Robogymnast. Moreover, a system simulation using MATLAB Simulink is conducted to show the impact of factors including overshoot, rising, and settling time. The principal objective of the study lies in investigating how a linear quadratic regulator or fuzzy logic controller with a linear quadratic regulator (FLQR) can be applied to the Robogymnast, and to assess system behaviour under five scenarios, namely the original value, this value plus or minus ±25%, and plus or minus ±50%. In order to further assess the performance of the controllers used, a comparison is made between the outcomes found here and findings in the recent literature with fuzzy linear quadratic regulator controllers.

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23

Yazici, Hakan, and Mert Sever. "Active control of a non-linear landing gear system having oleo pneumatic shock absorber using robust linear quadratic regulator approach." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 13 (June 14, 2017): 2397–411. http://dx.doi.org/10.1177/0954410017713773.

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This paper deals with the active control of a non-linear active landing gear system equipped with oleo pneumatic shock absorber. Runway induced vibration can cause reduction of pilot’s capability of control the aircraft and results the safety problem before take-off and after landing. Moreover, passenger–crew comfort is adversely affected by vertical vibrations of the fuselage. The active landing gears equipped with oleo pneumatic shock absorber are highly non-linear systems. In this study, uncertain polytopic state space representation is developed by modelling the pneumatic shock absorber dynamics as a mechanical system with non-linear stiffness and damping properties. Then, linear matrix inequalities-based robust linear quadratic regulator controller having pole location constraints is designed, since the classical linear quadratic regulator control design is dealing with linearized state space models without considering the non-linearities and uncertainties. Thereafter, numerical simulation studies are carried out to analyse aircraft response during taxiing. Bump- and random-type runway irregularities are used with various runway class and wide range of longitudinal speed. Simulation results revealed that neglecting the non-linear dynamics associated with oleo pneumatic shock absorber results significant performance degradation. Consequently, it is demonstrated that proposed robust linear quadratic regulator controller has a superior performance in terms of passenger–crew comfort and operational safety when compared to classical linear quadratic regulator.

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24

Tấn, Vũ Văn. "OPTIMAL CONTROLLER DESIGN FOR ACTIVE SUSPENSION SYSTEM ON CARS." TNU Journal of Science and Technology 225, no. 13 (November 30, 2020): 107–13. http://dx.doi.org/10.34238/tnu-jst.3559.

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Hệ thống treo là một trong những bộ phận quan trọng nhất trong thiết kế ô tô và là yếu tố quyết định đến sự thoải mái của lái xe, hành khách (độ êm dịu) và giữ được bám giữa lốp và mặt đường (độ an toàn). Bài báo này giới thiệu một mô hình ¼ ô tô có 2 bậc tự do sử dụng hệ thống treo chủ động với hai bộ điều khiển tối ưu: linear quadratic regulator và linear quadratic gaussian (linear quadratic regulator kết hợp với bộ quan sát Kalman-Bucy). Bằng cách sử dụng bộ quan sát Kalman-Bucy, số lượng cảm biến dùng để đo đạc các tín hiệu đầu vào của bộ điều khiển linear quadratic regulator đã được giảm thiểu tối đa chỉ còn các cảm biến thông thường như gia tốc của khối lượng được treo. Độ êm dịu và an toàn chuyển động khi ô tô sử dụng hệ thống treo chủ động được so sánh với ô tô sử dụng hệ thống treo bị động thông thường thông qua dịch chuyển của khối lượng được treo và gia tốc của nó. Kết quả mô phỏng đã thể hiện rõ giá trị sai lệch bình phương trung bình của gia tốc dịch chuyển thân xe với hệ thống treo tích cực điều khiển tối ưu linear quadratic regulator, linear quadratic gaussian đã giảm khoảng 20% so với ô tô sử dụng hệ thống treo bị động.

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25

Thanoon, Mohammad A., Sohaib R. Awad, and Ismael Kh Abdullah. "LQR controller design for stabilization of non-linear DIP system based on ABC algorithm." Eastern-European Journal of Enterprise Technologies 2, no. 2 (122) (April 17, 2023): 36–44. http://dx.doi.org/10.15587/1729-4061.2023.275657.

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Abstract:

Inverted pendulum systems, such as double or single, rotational or translational inverted pendulums are non-linear and unstable, which have been the most dominant approaches for control systems. The double inverted pendulum is one kind of a non-linear, unstable system, multivariable, and strong coupling with a wide range of control methods. To model these types of systems, many techniques have been proposed so that motivating researchers to come up with new innovative solutions. The Linear Quadratic Regulator (LQR) controller has been a common controller used in this field. Meanwhile, the Artificial Bee Colony (ABC) technique has become an alternative solution for employing Bee Swarm Intelligence algorithms. The research solutions of the artificial bee colony algorithm in the literature can be beneficial, however, the utilization of discovered sources of food is ineffective. Thus, in this paper, we aim to provide a double inverted pendulum system for stabilization by selecting linear quadratic regulator parameters using a bio-inspired optimization methodology of artificial bee colony and weight matrices Q and R. The results show that when the artificial bee colony algorithm is applied to a linear quadratic regulator controller, it gains the capacity to autonomously tune itself in an online process. To further demonstrate the efficiency and viability of the suggested methodology, simulations have been performed and compared to conventional linear quadratic regulator controllers. The obtained results demonstrate that employing artificial intelligence (AI) together with the proposed controller outperforms the conventional linear quadratic regulator controllers by more than 50 % in transient response and improved time response and stability performance

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26

Alonso, C. Amo, D. Ho, and J. M. Maestre. "Distributed Linear Quadratic Regulator Robust to Communication Dropouts." IFAC-PapersOnLine 53, no. 2 (2020): 3072–78. http://dx.doi.org/10.1016/j.ifacol.2020.12.1012.

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27

JOHNSON, C. D. "Limits of propriety for linear-quadratic regulator problems." International Journal of Control 45, no. 5 (May 1987): 1835–46. http://dx.doi.org/10.1080/00207178708933849.

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28

Zhang, Si Qi, Tian Xia Zhang, and Shu Wen Zhou. "Vehicle Dynamics Control Based on Linear Quadratic Regulator." Applied Mechanics and Materials 16-19 (October 2009): 876–80. http://dx.doi.org/10.4028/www.scientific.net/amm.16-19.876.

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The paper presents a vehicle dynamics control strategy devoted to prevent vehicles from spinning and drifting out. With vehicle dynamics control system, counter braking are applied at individual wheels as needed to generate an additional yaw moment until steering control and vehicle stability were regained. The Linear Quadratic Regulator (LQR) theory was designed to produce demanded yaw moment according to the error between the measured yaw rate and desired yaw rate. The results indicate the proposed system can significantly improve vehicle stability for active safety.

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29

Bender, D., and A. Laub. "The linear-quadratic optimal regulator for descriptor systems." IEEE Transactions on Automatic Control 32, no. 8 (August 1987): 672–88. http://dx.doi.org/10.1109/tac.1987.1104694.

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30

Grecksch, W., and V. V. Anh. "An Infinite-Dimensional Fractional Linear Quadratic Regulator Problem." Stochastic Analysis and Applications 30, no. 2 (March 2012): 203–19. http://dx.doi.org/10.1080/07362994.2012.649618.

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31

Das, Dibakar, Gurunath Gurrala, and U. Jayachandra Shenoy. "Linear Quadratic Regulator-Based Bumpless Transfer in Microgrids." IEEE Transactions on Smart Grid 9, no. 1 (January 2018): 416–25. http://dx.doi.org/10.1109/tsg.2016.2580159.

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32

Tasch, Uri, and Mark L. Nagurka. "Linear Quadratic Regulator With Varying Finite Time Durations." Journal of Dynamic Systems, Measurement, and Control 114, no. 3 (September 1, 1992): 517–19. http://dx.doi.org/10.1115/1.2897378.

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The optimal state trajectories of time-invariant linear quadratic regulator problems with different time horizons can be found from a single Riccati gain matrix shifted appropriately in time. This result has significant ramifications for real-time implementation of optimal controllers driving systems at various speeds.

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33

Bemporad, Alberto, Manfred Morari, Vivek Dua, and Efstratios N. Pistikopoulos. "The explicit linear quadratic regulator for constrained systems." Automatica 38, no. 1 (January 2002): 3–20. http://dx.doi.org/10.1016/s0005-1098(01)00174-1.

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34

Boukas, E. K., and Z. K. Liu. "Jump linear quadratic regulator with controlled jump rates." IEEE Transactions on Automatic Control 46, no. 2 (2001): 301–5. http://dx.doi.org/10.1109/9.905698.

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35

Possieri, Corrado, Mario Sassano, Sergio Galeani, and Andrew R. Teel. "The linear quadratic regulator for periodic hybrid systems." Automatica 113 (March 2020): 108772. http://dx.doi.org/10.1016/j.automatica.2019.108772.

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36

Cardenas Alzate, Pedro Pablo, German Correa Velez, and Fernando Mesa. "Optimum control using finite time quadratic linear regulator." Contemporary Engineering Sciences 11, no. 95 (2018): 4709–16. http://dx.doi.org/10.12988/ces.2018.89516.

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37

Zhang, D. M., L. Meng, X. G. Wang, and L. L. Ou. "Linear quadratic regulator control of multi-agent systems." Optimal Control Applications and Methods 36, no. 1 (November 11, 2013): 45–59. http://dx.doi.org/10.1002/oca.2100.

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38

Helmy, M., A. T. Hafez, and M. Ashry. "CubeSat attitude control via linear quadratic regulator (LQR)." Journal of Physics: Conference Series 2616, no. 1 (November 1, 2023): 012022. http://dx.doi.org/10.1088/1742-6596/2616/1/012022.

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Abstract The interest in space-related activities has grown recently on a global scale. The determination and control of attitude are necessary all space duties. As it affects the satellites mission accuracy, many researches are related to it. Attitude control systems (ACS) design and modelling are represented in this paper. The mathematical models for CubeSat and reaction wheels that act as actuator and the proposed optimal control system are introduced. The proposed controller is applied to control and stabilize the CubeSat through a set of reaction wheels. The simulation results show the superior results of the proposed controller compared with traditional control systems in the presence of external disturbances and white noise. The withdraws of each control system are presented through the simulation results. The main contribution in this paper is solving the attitude control problem for a CubeSat using LQR approach in the presences of disturbances and noise.

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39

Dibyo Laksono, Heru, and M. Reza Permana. "Analisa Performansi Sistem Kendali Frekuensi Tenaga Listrik Multimesin Dengan Metoda Linear Quadratic Regulator (LQR)." Jurnal Nasional Teknik Elektro 3, no. 2 (September 1, 2014): 167–76. http://dx.doi.org/10.20449/jnte.v3i2.82.

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40

Adel, Bouchahed, Assabaa Mohamed, Draidi Abdellah, Makhloufi Fateh, and Belhani Ahmed. "Improvement of the linear quadratic regulator control applied to a DC-DC boost converter driving a permanent magnet direct current motor." Improvement of the linear quadratic regulator control applied to a DC-DC boost converter driving a permanent magnet direct current motor 13, no. 6 (December 1, 2023): 6131–40. https://doi.org/10.11591/ijece.v13i6.pp6131-6140.

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This article discusses a new robust control technique that enables the DC-DC boost converter driving a permanent magnet direct current (PMDC) motor to operate in high static and dynamic performances. The new technique is based on the design of a both linear quadratic regulator (LQR) and linear quadratic regulator-proportional integral (LQR-PI) type controllers, which have the advantage of eliminating oscillations, overshoots and fluctuations on different characteristics in steady-state system operation. In order to increase the output voltage, the LQR regulator is combined with a first-order system represented in the form of a closed-loop transfer function, the latter raising the output voltage to 24 volts, this voltage is enough to drive the permanent magnet direct current motor. The contribution of this paper is the creation of a robust control system represented in the form of a hybrid corrector able to regulate steadystate and transient disturbances and oscillations as well as to increase DC-DC boost converter output voltage for the PMDC motor to operate at rated voltage. The results of the three control techniques are validated by MATLAB Simulink.

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41

Shauqee, Mohamad Norherman, Parvathy Rajendran, and Nurulasikin Mohd Suhadis. "Proportional Double Derivative Linear Quadratic Regulator Controller Using Improvised Grey Wolf Optimization Technique to Control Quadcopter." Applied Sciences 11, no. 6 (March 17, 2021): 2699. http://dx.doi.org/10.3390/app11062699.

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A hybrid proportional double derivative and linear quadratic regulator (PD2-LQR) controller is designed for altitude (z) and attitude (roll, pitch, and yaw) control of a quadrotor vehicle. The derivation of a mathematical model of the quadrotor is formulated based on the Newton–Euler approach. An appropriate controller’s parameter must be obtained to obtain a superior control performance. Therefore, we exploit the advantages of the nature-inspired optimization algorithm called Grey Wolf Optimizer (GWO) to search for those optimal values. Hence, an improved version of GWO called IGWO is proposed and used instead of the original one. A comparative study with the conventional controllers, namely proportional derivative (PD), proportional integral derivative (PID), linear quadratic regulator (LQR), proportional linear quadratic regulator (P-LQR), proportional derivative and linear quadratic regulator (PD-LQR), PD2-LQR, and original GWO-based PD2-LQR, was undertaken to show the effectiveness of the proposed approach. An investigation of 20 different quadcopter models using the proposed hybrid controller is presented. Simulation results prove that the IGWO-based PD2-LQR controller can better track the desired reference input with shorter rise time and settling time, lower percentage overshoot, and minimal steady-state error and root mean square error (RMSE).

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42

Yan, Xiao, Zhao-Dong Xu, and Qing-Xuan Shi. "Fuzzy neural network control algorithm for asymmetric building structure with active tuned mass damper." Journal of Vibration and Control 26, no. 21-22 (February 27, 2020): 2037–49. http://dx.doi.org/10.1177/1077546320910003.

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Asymmetric structures experience torsional effects when subjected to seismic excitation. The resulting rotation will further aggravate the damage of the structure. A mathematical model is developed to study the translation and rotation response of the structure during seismic excitation. The motion equations of the structures which cover the translation and rotation are obtained by the theoretical derivations and calculations. Through the simulated computation, the translation and rotation response of the structure with the uncontrolled system, the tuned mass damper control system, and active tuned mass damper control system using linear quadratic regulator algorithm are compared to verify the effectiveness of the proposed active control system. In addition, the linear quadratic regulator and fuzzy neural network algorithm are used to the active tuned mass damper control system as a contrast group to study the response of the structure with different active control method. It can be concluded that the structure response has a significant reduction by using active tuned mass damper control system. Furthermore, it can be also found that fuzzy neural network algorithm can replace the linear quadratic regulator algorithm in an active control system. Because fuzzy neural network algorithm can control the process on an uncertain mathematical model, it has more potential in practical applications than the linear quadratic regulator control method.

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Fikri, Muhamad Rausyan, and Djati Wibowo Djamari. "Full-State Feedback Control Design for Shape Formation using Linear Quadratic Regulator." Indonesian Journal of Computing, Engineering and Design (IJoCED) 2, no. 2 (October 1, 2020): 83. http://dx.doi.org/10.35806/ijoced.v2i2.114.

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This study investigated the capability of a group of agents to form a desired shape formation by designing the feedback control using a linear quadratic regulator. In real application, the state condition of agents may change due to some particular problems such as a slow input response. In order to compensate for the problem that affects agent-to-agent coordination, a robust regulator was implemented into the formation algorithm. In this study, a linear quadratic regulator as the full-state feedback of robust regulator method for shape formation was considered. The result showed that a group of agents can form the desired shape (square) formation with a modification of the trajectory shape of each agent. The results were validated through numerical experiments.

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Bigaliyeva, A. Z. "Development of linear-quadratic-gaussian control of the technological process of fine grinding." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 95, no. 1 (March 30, 2025): 60–71. https://doi.org/10.47533/2025.1606-146x.04.

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The paper is dedicated to research of grinding process in a planetary ball mill. The possibility of continuous control of fineness of grinding with the usage of optimization methods is taken into consideration. The mathematical representation of an object had been built to consider it as the mathematical model. The comparison of given model to data of natural experiments is performed. In the paper, the results of analysis of the main quality points from mathematical model are included. On the model base the linear- quadratic regulator LQG is synthesized, which represents the combination of the Kalman filter The Linear Quadratic Estimation (LQE) along with The Linear Quadratic Estimation (LQR). The regulator is used to achieve the main task – keeping up of strictly defined range in predefined class output by controlling incoming flow in the ball mill. In the paper general enunciation of Linear Quadratic Gaussian (LQG) is described along with the engineering procedures and all necessary hypothesis. The obtained results from modeling of LQG controller are shown.

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Amertet Finecomes, Sairoel, Fisseha L. Gebre, Abush M. Mesene, and Solomon Abebaw. "Optimization of automobile active suspension system using minimal order." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (June 1, 2022): 2378. http://dx.doi.org/10.11591/ijece.v12i3.pp2378-2392.

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<p><span>This paper presents an analysis and design of linear quadratic regulator for reduced order full car suspension model incorporating the dynamics of the actuator to improve system performance, aims at benefiting: Ride comfort, long life of vehicle, and stability of vehicle. Vehicle’s road holding or handling and braking for good active safety and driving pleasure, and keeping vehicle occupants comfortable and reasonably well isolated from road noise, bumps, and vibrations are become a key research area conducted by many researchers around the globe. Different researchers were tested effectiveness of different controllers for different vehicle model without considering the actuator dynamics. In this paper full vehicle model was reduced to a minimal order using minimal realization technique. The entire system responses were simulated in MATLAB/Simulink environment. The effectiveness of linear quadratic regulator controller was compared for the system model with and without actuator dynamics for different road profiles. The simulation results were indicated that percentage reduction in the peak value of vertical and horizontal velocity for the linear quadratic regulator with actuator dynamics relative to linear quadratic regulator without actuator dynamics was 28.57%. Overall simulation results were demonstrated that proposed control scheme has able to improve the effectiveness of the car model for both ride comfort and stability.</span></p>

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Liu, Xiaoxiao, YuanSheng Wang, and XingMin Ren. "Optimal vibration control of moving-mass beam systems with uncertainty." Journal of Low Frequency Noise, Vibration and Active Control 39, no. 3 (April 22, 2019): 803–17. http://dx.doi.org/10.1177/1461348419844150.

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A linear optimal regulator for uncertain system is designed through the application of the probability density evolution method to linear quadratic regulator controller. One important background of this work is bridge-vehicle/gun-projectile system. This type of optimal problem is currently transformed into a moving load problem. The developed optimal regulator can provide the law of probability densities of outputs varying with time. In order to make the advocated method reach an optimal performance, the beneficial weighting matrix pair (Q, R) is selected using a trade-off sense. The designed regulator is then applied to a coupled simply supported beam-moving mass system, choosing the mid-span deflection as an output response and considering stochastic system parameters. The numerical example shows that the robustness of the proposed optimal regulator cannot be overestimated in comparison with a deterministic linear quadratic regulator controller. Further, the proposed method can produce an efficient solution channel for modern optimal control theory, especially, when compared with different uncertain optimal control techniques.

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Kudinov, Y. I., E. S. Duvanov, I. Y. Kudinov, A. F. Pashchenko, F. F. Pashchenko, G. A. Pikina, A. V. Andryushin, E. K. Arakelyan, and S. V. Mezin. "Construction and Analysis of Adaptive Fuzzy Linear Quadratic Regulator." Journal of Physics: Conference Series 1683 (December 2020): 042065. http://dx.doi.org/10.1088/1742-6596/1683/4/042065.

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Ohta, H., M. Kakinuma, and P. N. Nikiforuk. "Use of negative weights in linear quadratic regulator synthesis." Journal of Guidance, Control, and Dynamics 14, no. 4 (July 1991): 791–96. http://dx.doi.org/10.2514/3.20714.

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Luo, Jia, and C. Edward Lan. "Determination of weighting matrices of a linear quadratic regulator." Journal of Guidance, Control, and Dynamics 18, no. 6 (November 1995): 1462–63. http://dx.doi.org/10.2514/3.21569.

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GERAY, OKAN, and DOUGLAS P. LOOZE. "Linear quadratic regulator loop shaping for high frequency compensation." International Journal of Control 63, no. 6 (April 1996): 1055–68. http://dx.doi.org/10.1080/00207179608921883.

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