Journal articles: 'Linear Quadratic Gaussian (LQG) control'

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Likaj, Rame, and Ahmet Shala. "Optimisation and Control of Vehicle Suspension Using Linear Quadratic Gaussian Control." Strojnícky casopis – Journal of Mechanical Engineering 68, no. 1 (April 1, 2018): 61–68. http://dx.doi.org/10.2478/scjme-2018-0006.

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Abstract The paper deals with the optimal design and analysis of quarter car vehicle suspension system based on the theory of linear optimal control because Linear Quadratic Gaussian (LQG) offers the possibility to emphasize quantifiable issues like ride comfort or road holding very easily by altering the weighting factor of a quadratic criterion. The theory used assumes that the plant (vehicle model + road unevenness model) is excited by white noise with Gaussian distribution. The term quadratic is related to a quadratic goal function. The goal function is chosen to provide the possibility to emphasize three main objectives of vehicle suspensions; ride comfort, suspension travel and road holding. Minimization of this quadratic goal function results in a law of feedback control. For optimal designs are used the optimal parameters which have been derived by comparison of two optimisation algorithms: Sequential Quadratic Program (SQP) and Genetic Algorithms (GA's), for a five chosen design parameters. LQG control is considered to control active suspension for the optimal parameters derived by GA's, while the main focus is to minimise the vertical vehicle body acceleration

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Kim, Beom-Soo, Young-Joong Kim, and Myo-Taeg Lim. "LQG Control for Nonstandard Singularly Perturbed Discrete-Time Systems." Journal of Dynamic Systems, Measurement, and Control 126, no. 4 (December 1, 2004): 860–64. http://dx.doi.org/10.1115/1.1850537.

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In this paper we present a control method and a high accuracy solution technique in solving the linear quadratic Gaussian problems for nonstandard singularly perturbed discrete time systems. The methodology that exists in the literature for the solution of the standard singularly perturbed discrete time linear quadratic Gaussian optimal control problem cannot be extended to the corresponding nonstandard counterpart. The solution of the linear quadratic Gaussian optimal control problem is obtained by solving the pure-slow and pure-fast reduced-order continuous-time algebraic Riccati equations and by implementing the pure-slow and pure-fast reduced-order Kalman filters. In order to show the effectiveness of the proposed method, we present the numerical result for a one-link flexible robot arm.

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Roux, G., B. Dahhou, K. Najim, and I. Queinnec. "Adaptive linear quadratic gaussian (LQG) control of a bioreactor." Journal of Chemical Technology & Biotechnology 53, no. 2 (April 24, 2007): 133–41. http://dx.doi.org/10.1002/jctb.280530205.

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Ingabire, Aline, and Andrey A. Sklyarov. "Control of longitudinal flight dynamics of a fixedwing UAV using LQR, LQG and nonlinear control." E3S Web of Conferences 104 (2019): 02001. http://dx.doi.org/10.1051/e3sconf/201910402001.

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This paper aim is to present a comparative study between Linear Quadratic Regulator (LQR), Linear Quadratic Gaussian (LQG) and nonlinear controllers for pitch control of a fixed-wing Unmanned Aerial Vehicle (UAV). Due to a good stability margin and strong robustness LQR has been selected. LQG was chosen because is able to overcome external disturbances. Kalman Filter controller was also introduced to the fixed-wing UAV flight control. Further, we designed an autopilot that controls the pitch angle of the fixed-wing UAV. In the end, the control laws are simulated in Matlab/Simulink. The results obtained are compared to see which method is faster, more reliable and more robust.

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Zulkarnain, Noraishikin, Hairi Zamzuri, and Saiful Amri Mazlan. "LQG Control Design for Vehicle Active Anti-Roll Bar System." Applied Mechanics and Materials 663 (October 2014): 146–51. http://dx.doi.org/10.4028/www.scientific.net/amm.663.146.

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The objective of this paper is to design a linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers for an active anti-roll bar system. The use of an active anti-roll bar will be analysed from two different perspectives in vehicle ride comfort and handling performances. This paper proposed the basic vehicle dynamic modelling with four degree of freedom (DOF) on half car model and are described that show, why and how it is possible to control the handling and ride comfort of the car, with the external forces also control strategies on the front anti-roll bar. By simulation analysis, the design model is validity and the performance under control of linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controller are achieved. Both two controllers are modeled in MATLAB/SIMULINK environment. It has to be determined which control strategy delivers better performance with respect to roll angle and the roll rate of half vehicle body. The result shows, however, that LQG produced better response compared to a LQR strategy.

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ATANOV, S. K., and А. Z. BIGALIYEVA. "Synthesis of LQG regulator for intelligent control of the technological process of fine grinding." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 4, no. 78 (December 15, 2020): 22–27. http://dx.doi.org/10.47533/2020.1606-146x.28.

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The article presents the development of a linear-quadratic Gaussian controller (LQG) for intelligent control of the fine grinding technological process. The LQG regulator was designed to control the quality of mill output. The developed LQG controller takes into account external disturbances (process noise) and noise in measurements modeled as white noise with a Gaussian distribution. The controller is developed on the basis of a combination of a stationary linear quadratic controller (LQR) and estimation of the state of the Kalman filter (LQE) in the stationary state by solving the matrix Riccati equation in order to determine the feedback gain and Kalman gain. In the course of work: a mathematical model of the grinding process is built, an analysis of the frequency characteristics of the obtained model is made; the model was checked for stability, controllability, and observability; on the basis of the model, the LQG regulator was synthesized. Transient process characteristics confirm precise control. Modeling is implemented in the MATLAB environment.

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ATANOV, S. K., and А. Z. BIGALIYEVA. "Synthesis of LQG regulator for intelligent control of the technological process of fine grinding." Bulletin of the National Engineering Academy of the Republic of Kazakhstan 4, no. 78 (December 15, 2020): 22–27. http://dx.doi.org/10.47533/2020.1606-146x.28.

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The article presents the development of a linear-quadratic Gaussian controller (LQG) for intelligent control of the fine grinding technological process. The LQG regulator was designed to control the quality of mill output. The developed LQG controller takes into account external disturbances (process noise) and noise in measurements modeled as white noise with a Gaussian distribution. The controller is developed on the basis of a combination of a stationary linear quadratic controller (LQR) and estimation of the state of the Kalman filter (LQE) in the stationary state by solving the matrix Riccati equation in order to determine the feedback gain and Kalman gain. In the course of work: a mathematical model of the grinding process is built, an analysis of the frequency characteristics of the obtained model is made; the model was checked for stability, controllability, and observability; on the basis of the model, the LQG regulator was synthesized. Transient process characteristics confirm precise control. Modeling is implemented in the MATLAB environment.

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Djaballah, Farid, M. A. Si Mohammed, and Nabil Boughanmi. "An implementation of optimal control methods (LQI, LQG, LTR) for geostationary satellite attitude control." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 6 (December 1, 2019): 4728. http://dx.doi.org/10.11591/ijece.v9i6.pp4728-4737.

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This paper investigates a new strategy for geostationary satellite attitude control using Linear Quadratic Gaussian (LQG), Loop Transfer Recovery (LTR), and Linear Quadratic Integral (LQI) control techniques. The sub-system satellite attitude determination and control of a geostationary satellite in the presence of external disturbances, the dynamic model of sub-satellite motion is firstly established by Euler equations. During the flight mission at 35000 Km attitude, the stability characteristics of attitude motion are analyzed with a large margin error of pointing, then a height performance-order LQI, LQG and LTR attitude controller are proposed to achieve stable control of the sub-satellite attitude, which dynamic model is linearized by using feedback linearization method. Finally, validity of the LTR order controller and the advantages over an integer order controller are examined by numerical simulation. Comparing with the corresponding integer order controller (LQI, LQG), numerical simulation results indicate that the proposed sub-satellite attitude controller based on LTR order can not only stabilize the sub-satellite attitude, but also respond faster with smaller overshoot.

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Lee, C. S., W. L. Chan, S. S. Jan, and F. B. Hsiao. "A linear-quadratic-Gaussian approach for automatic flight control of fixed-wing unmanned air vehicles." Aeronautical Journal 115, no. 1163 (January 2011): 29–41. http://dx.doi.org/10.1017/s0001924000005340.

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AbstractThis paper presents the design and implementation of automatic flight controllers for a fixed-wing unmanned air vehicle (UAV) by using a linear-quadratic-Gaussian (LQG) control approach. The LQG design is able to retain the guaranteed closed-loop stability of the linear-quadratic regulator (LQR) while having incomplete state measurement. Instead of feeding back the actual states to form the control law, the estimated states provided by a separately designed optimal observer, i.e. the Kalman filter are used. The automatic flight controllers that include outer-loop controls are constructed based on two independent LQG regulators which govern the longitudinal and lateral dynamics of the UAV respectively. The resulting controllers are structurally simple and thus efficient enough to be easily realized with limited onboard computing resource. In this paper, the design of the LQG controllers is described while the navigation and guidance algorithm based on Global Positioning System (GPS) data is also outlined. In order to validate the performance of the automatic flight control system, a series of flight tests have been conducted. Significant results are presented and discussed in detail. Overall, the flight-test results show that it is highly feasible and effective to apply the computationally efficient LQG controllers on a fixed-wing UAV system with a relatively simple onboard system. On the other hand, a fully automatic 44km cross-sea flight demonstration was successfully conducted using the LQG-based flight controllers. Detailed description regarding the event and some significant flight data are given.

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Liu, Qing-Quan, and Fang Jin. "LQG Control of Networked Control Systems with Limited Information." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/206391.

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This paper addresses linear quadratic Gaussian (LQG) control problems for multi-input multioutput (MIMO), linear time-invariant (LTI) systems, where the sensors and controllers are geographically separated and connected via a digital communication channel with limited data rates. An observer-based, quantized state feedback control scheme is employed in order to achieve the minimum data rate for mean square stabilization of the unstable plant. An explicit expression is presented to state the tradeoff between the LQ cost and the data rate. Sufficient conditions on the data rate for mean square stabilization are derived. An illustrative example is given to demonstrate the effectiveness of the proposed scheme.

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Balabanov, Aleksey, Todor Stoilov, and Yordanka Boneva. "Linear-Quadratic-Gaussian Optimization of Urban Transportation Network with Application to Sofia Traffic Optimization." Cybernetics and Information Technologies 16, no. 3 (September 1, 2016): 165–84. http://dx.doi.org/10.1515/cait-2016-0041.

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Abstract The paper defines and solves a Linear-Quadratic-Gaussian (LQG) optimization problem addressing real time control policy of Urban Transportation Network (UTN). The paper presents UTN model definition, analysis and LQG optimization problem definition, resulting in special problem structure. A real application for UTN situated in Sofia, Bulgaria along Yosif Gurko street was provided for testing this control policy.

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Sivrioglu, Selim, and Fevzi Cakmak Bolat. "Switching linear quadratic Gaussian control of a flexible blade structure containing magnetorheological fluid." Transactions of the Institute of Measurement and Control 42, no. 3 (October 15, 2019): 618–27. http://dx.doi.org/10.1177/0142331219878956.

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The present study suggests a new active control structure with a switching algorithm for control current of the electromagnetic actuator to suppress vibrations of a flexible blade element containing magnetorheological (MR) fluid. An identification model between MR fluid inside the blade and the electromagnetic actuator is utilized to derive the force equation. Since only one electromagnet is employed to suppress the blade vibration, a single-sided control actuation occurs in the proposed system. Therefore, the pulling force used for vibration control is generated by the actuator when the blade moves to downward direction. A switching linear quadratic Gaussian (LQG) controller that produces always a positive control input is designed to attenuate the blade vibrations. The LQG controller with switching is experimentally implemented under the impact and steady-state aerodynamic disturbances. The results of experiments show that the proposed switching controller is effective to attenuate vibrations of the flexible blade element.

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Huang, Jianhui, Xun Li, and Tianxiao Wang. "Mean-Field Linear-Quadratic-Gaussian (LQG) Games for Stochastic Integral Systems." IEEE Transactions on Automatic Control 61, no. 9 (September 2016): 2670–75. http://dx.doi.org/10.1109/tac.2015.2506620.

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Li, Haisheng, Rongxuan Li, and Feng Wu. "A New Control Performance Evaluation Based on LQG Benchmark for the Heating Furnace Temperature Control System." Processes 8, no. 11 (November 9, 2020): 1428. http://dx.doi.org/10.3390/pr8111428.

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Temperature control systems are a series of processes with large time-delay and non-linear characteristics. Research shows that using fractional-order modeling and corresponding control strategies can better control these processes. At the same time, the existing studies for control performance assessment are almost committed to the integer order control systems, and the methods used in few literatures on performance assessment of fractional order systems are also one-sided. This paper applies the linear quadratic Gaussian (LQG) evaluation benchmark to the performance evaluation of fractional-order control systems for the first time, starting with the LQG evaluation benchmark considering the input and output performance. The LQG benchmark can be obtained by the analytical algorithm, which simplifies the complexity of LQG solution. Finally, taking the application of the fractional predictive function control (FO-PFC) controller in the experiment of industrial heating furnace temperature control as an example, the effectiveness of the LQG benchmark is verified.

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Lee, C. S., F. B. Hsiao, and S. S. Jan. "Design and implementation of linear-quadratic-Gaussian stability augmentation autopilot for unmanned air vehicle." Aeronautical Journal 113, no. 1143 (May 2009): 275–90. http://dx.doi.org/10.1017/s0001924000002955.

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Abstract The linear-quadratic-Gaussian (LQG) control synthesis has the advantage of dealing with the uncertain linear systems disturbed by additive white Gaussian noise while having incomplete system state information available for control-loop feedback. This paper hence explores the feasibility of designing and implementing a stability augmentation autopilot for fixed-wing unmanned air vehicles using the LQG approach. The autopilot is composed of two independently designed LQG controllers which control the longitudinal and lateral motions of the aircraft respectively. The corresponding linear models are obtained through a system identification routine which makes use of the combination of two well-established identification methods, namely the subspace method and prediction error method. The two identification methods complement each other well and this paper shows that the proposed system identification scheme is capable of attaining satisfactory state-space models. A complete autopilot design procedure is devised and it is shown that the design process is simple and effective. Resulting longitudinal and lateral controllers are successfully verified in computer simulations and actual flight tests. The flight test results are presented in the paper and they are found to be consistent with the simulation results.

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Gnecco, Giorgio, Alberto Bemporad, Marco Gori, and Marcello Sanguineti. "LQG Online Learning." Neural Computation 29, no. 8 (August 2017): 2203–91. http://dx.doi.org/10.1162/neco_a_00976.

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Optimal control theory and machine learning techniques are combined to formulate and solve in closed form an optimal control formulation of online learning from supervised examples with regularization of the updates. The connections with the classical linear quadratic gaussian (LQG) optimal control problem, of which the proposed learning paradigm is a nontrivial variation as it involves random matrices, are investigated. The obtained optimal solutions are compared with the Kalman filter estimate of the parameter vector to be learned. It is shown that the proposed algorithm is less sensitive to outliers with respect to the Kalman estimate (thanks to the presence of the regularization term), thus providing smoother estimates with respect to time. The basic formulation of the proposed online learning framework refers to a discrete-time setting with a finite learning horizon and a linear model. Various extensions are investigated, including the infinite learning horizon and, via the so-called kernel trick, the case of nonlinear models.

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Kim, Young Moon, Ki Pyo You, and Jang Youl You. "LQG Control of Across-Wind Response of a Tall Building with AMD." Advanced Materials Research 1004-1005 (August 2014): 1602–7. http://dx.doi.org/10.4028/www.scientific.net/amr.1004-1005.1602.

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Modern tall buildings are more flexible so occur excessive wind-induced vibration resulting in occupant discomfort and structural safety. Many studies to reduce such a wind-induced vibration using a feedback controller and auxiliary devices have been conducted .The optimal control law of linear quadratic Gaussian (LQG) controller is used for reducing the across-wind vibration response of a tall building with an active mass damper (AMD). Fluctuating across-wind load treated as a Gaussian white noise process is simulated numerically in time domain. And using this simulated across-wind load estimated across-wind vibration responses of tall building with AMD using LQG controller.

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Tayebi, Javad, Amir Ali Nikkhah, and Jafar Roshanian. "LQR/LQG attitude stabilization of an agile microsatellite with CMG." Aircraft Engineering and Aerospace Technology 89, no. 2 (March 6, 2017): 290–96. http://dx.doi.org/10.1108/aeat-07-2014-0102.

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Purpose The purpose of the paper is to design a new attitude stabilization system for a microsatellite based on single gimbal control moment gyro (SGCMG) in which the gimbal rates are selected as controller parameters. Design/methodology/approach In the stability mode, linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) control strategies are presented with the gimbal rates as a controller parameters. Instead of developing a control torque to solve the attitude problem, the attitude controller is developed in terms of the control moment gyroscope gimbal angular velocities. Attitude control torques are generated by means of a four SGCMG pyramid cluster. Findings Numerical simulation results are provided to show the efficiency of the proposed controllers. Simulation results show that this method could stabilize satellite from initial condition with large angles and with more accuracy in comparison with feedback quaternion and proportional-integral-derivative controllers. These results show the effect of filtering the noisy signal in the LQG controller. LQG in comparison to LQR is more realistic. Practical implications The LQR method is more appropriate for the systems that have project models reasonably exact and ideal sensors/actuators. LQG is more realistic, and it can be used when not all of the states are available or when the system presents noises. LQR/LQG controller can be used in the stabilization mode of satellite attitude control. Originality/value The originality of this paper is designing a new attitude stabilization system for an agile microsatellite using LQR and LQG controllers.

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Ulsoy, A. G., D. Hrovat, and T. Tseng. "Stability Robustness of LQ and LQG Active Suspensions." Journal of Dynamic Systems, Measurement, and Control 116, no. 1 (March 1, 1994): 123–31. http://dx.doi.org/10.1115/1.2900666.

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A two-degree-of-freedom quarter-car model is used as the basis for linear quadratic (LQ) and linear quadratic Gaussian (LQG) controller design for an active suspension. The LQ controller results in the best rms performance trade-offs (as defined by the performance index) between ride, handling and packaging requirements. In practice, however, all suspension states are not directly measured, and a Kalman filter can be introduced for state estimation to yield an LQG controller. This paper (i) quantifies the rms performance losses for LQG control as compared to LQ control, and (ii) compares the LQ and LQG active suspension designs from the point of view of stability robustness. The robustness of the LQ active suspensions is not necessarily good, and depends strongly on the design of a backup passive suspension in parallel with the active one. The robustness properties of the LQG active suspension controller are also investigated for several distinct measurement sets.

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MIRZA, K. Z. "Linear Quadratic Gaussian Regulator for the Nonlinear Observer-Based Control of a Dynamic Base Inverted Pendulum." INCAS BULLETIN 13, no. 3 (September 4, 2021): 79–90. http://dx.doi.org/10.13111/2066-8201.2021.13.3.7.

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The inverted pendulum is a non-linear control problem permanently tending towards instability. The main aim of this study is to design a controller capable enough to work within the given conditions while also keeping the pendulum erect given the impulsive movement of the cart to which it is joint via a hinge. The first half of the paper presents the mathematical modelling of the dynamic system, together with the design of a linear quadratic regulator (LQR). This paper also discusses a novel adaptive control mechanism employing a Kalman filter for the mobile inverted pendulum system (MIPS). In the second half of the paper, a Gaussian Quadratic Linear Controller (LQG) is adapted to improve on previous deficiencies. The simulation is done through Simulink and results show that both controllers are capable of managing the multiple output model. However, data from simulations clearly showed that an LQG controller is a better choice.

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Lee, Kibeom, Seungmin Jeon, Heegwon Kim, and Dongsuk Kum. "Optimal Path Tracking Control of Autonomous Vehicle: Adaptive Full-State Linear Quadratic Gaussian (LQG) Control." IEEE Access 7 (2019): 109120–33. http://dx.doi.org/10.1109/access.2019.2933895.

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Camino, J. F., and I. F. Santos. "A periodic linear–quadratic controller for suppressing rotor-blade vibration." Journal of Vibration and Control 25, no. 17 (June 6, 2019): 2351–64. http://dx.doi.org/10.1177/1077546319853358.

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This paper presents an active control strategy, based on a time-varying linear–quadratic optimal control problem, to attenuate the tip vibration of a two-dimensional coupled rotor-blade system whose dynamics is periodic. First, a periodic full-state feedback controller based on the linear–quadratic regulator (LQR) problem is designed. If all the states are not available for feedback, then an optimal periodic time-varying estimator, using the Kalman–Bucy filter, is computed. Both the Kalman filter gain and the LQR gain are obtained as the solution of a periodic Riccati differential equation (PRDE). Together, these gains provide the observer-based linear–quadratic–Gaussian (LQG) controller. An algorithm to solve the PRDE is also presented. Both controller designs ensure closed-loop stability and performance for the linear time-varying rotor-blade equation of motion. Numerical simulations show that the LQR and the LQG controllers are able to significantly attenuate the rotor-blade tip vibration.

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Wang, Jiaying, Youming Guo, Lin Kong, Lanqiang Zhang, Naiting Gu, Kele Chen, and Changhui Rao. "Automatic disturbance identification for linear quadratic Gaussian control in adaptive optics." Monthly Notices of the Royal Astronomical Society 496, no. 4 (July 17, 2020): 5126–38. http://dx.doi.org/10.1093/mnras/staa1698.

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ABSTRACT Linear quadratic Gaussian (LQG) control is an appealing control strategy to mitigate disturbances in adaptive optics (AO) systems. The key of this method is to quickly and consecutively build an accurate dynamical model to track time-varying disturbances such as turbulence, wind load and vibrations. In order to address this problem, we propose an automatic identification method consisting mainly of an improved spectrum separation procedure and a parameter optimization process based on the particle swarm optimization (PSO) algorithm. The improved spectrum separation can pick out perturbation peaks more accurately, especially when some peaks are very close together. Moreover, compared with the Levenberg–Marquardt method and the maximum-likelihood technique based on grids, the PSO algorithm has a faster convergence speed and lower computational burden, and thus is easier to implement. The entire identification process can run automatically online without human intervention. This identification method is verified with a synthetic disturbance profile in a simulation. Furthermore, the performance of the method is evaluated with consecutive measurement data recorded by the 1-m New Vacuum Solar Telescope at the Fuxian Solar Observatory.

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Huang, Jianhui, Shujun Wang, and Zhen Wu. "Backward Mean-Field Linear-Quadratic-Gaussian (LQG) Games: Full and Partial Information." IEEE Transactions on Automatic Control 61, no. 12 (December 2016): 3784–96. http://dx.doi.org/10.1109/tac.2016.2519501.

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Sheng, Yan, Chao Wang, Ying Pan, and Xinhua Zhang. "Modified LQG/LTR Control Methodology in Active Structural Control." Journal of Low Frequency Noise, Vibration and Active Control 22, no. 2 (June 2003): 97–108. http://dx.doi.org/10.1260/026309203322770347.

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This paper presents a new active structural control design methodology comparing the conventional linear-quadratic-Gaussian synthesis with a loop-transfer-recovery (LQG/LTR) control approach for structures subjected to ground excitations. It results in an open-loop stable controller. Also the closed-loop stability can be guaranteed. More importantly, the value of the controller's gain required for a given degree of LTR is orders of magnitude less than what is required in the conventional LQG/LTR approach. Additionally, for the same value of gain, the proposed controller achieves a much better degree of recovery than the LQG/LTR-based controller. Once this controller is obtained, the problems of control force saturation are either eliminated or at least dampened, and the controller band-width is reduced and consequently the control signal to noise ratio at the input point of the dynamic system is increased. Finally, numerical examples illustrate the above advantages.

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Song, Q., J. Wilkie, and M. J. Grimble. "Robust Controller for Gas Turbines Based Upon LQG/LTR Design With Self-Tuning Features." Journal of Dynamic Systems, Measurement, and Control 115, no. 3 (September 1, 1993): 569–71. http://dx.doi.org/10.1115/1.2899141.

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A feasibility study is described for the design of a self-tuning controller for gas turbines with the multivariable discrete-time robust controller designed using a Linear Quadratic Gaussian/ Loop Transfer Recovery (LQG/LTR) design approach.

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OR, A. C., L. CORTELEZZI, and J. L. SPEYER. "Robust feedback control of Rayleigh–Bénard convection." Journal of Fluid Mechanics 437 (June 22, 2001): 175–202. http://dx.doi.org/10.1017/s0022112001004256.

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We investigate the application of linear-quadratic-Gaussian (LQG) feedback control, or, in modern terms, [Hscr ]2 control, to the stabilization of the no-motion state against the onset of Rayleigh–Bénard convection in an infinite layer of Boussinesq fluid. We use two sensing and actuating methods: the planar sensor model (Tang & Bau 1993, 1994), and the shadowgraph model (Howle 1997a). By extending the planar sensor model to the multi-sensor case, it is shown that a LQG controller is capable of stabilizing the no-motion state up to 14.5 times the critical Rayleigh number. We characterize the robustness of the controller with respect to parameter uncertainties, unmodelled dynamics. Results indicate that the LQG controller provides robust performances even at high Rayleigh numbers.

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Mitov, Alexander, Jordan Kralev, Tsonyo Slavov, and Ilcho Angelov. "Comparison of Model Predictive Control (MPC) and Linear-Quadratic Gaussian (LQG) Algorithm for Electrohydraulic Steering Control System." E3S Web of Conferences 207 (2020): 04001. http://dx.doi.org/10.1051/e3sconf/202020704001.

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The paper compares the performance of two embedded controllers applied in electrohydraulic steering systems – model predictive controller (MPC) and linear-quadratic Gaussian (LQG) controller with Kalman filtering for state estimation. Both controllers are designed on the basis of single input multiple output “black box” model obtained via identification approach. The controllers are implemented into industrial logic controller for mobile applications and their workability is experimentally checked with a laboratory model of a steering system for non-road mobile machinery. The results corresponding to investigation of performance of the closed-loop system are presented.

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Kim, Young Moon, Ki Pyo You, and Jang Youl You. "LQG Control of Across-Wind Response of a Tall Building." Advanced Materials Research 823 (October 2013): 396–401. http://dx.doi.org/10.4028/www.scientific.net/amr.823.396.

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Modern tall buildings using high strength and lighter construction materials are more flexible so could be excessive wind-induced vibrations resulting in occupant discomfort and structural unsafety . Recently, many studies have been advanced in using actuator force as an active control force based on the linear quadratic optimum control theory. It needs to predict the wind-induced response and the optimum control force to reduce the excessive wind-induced vibration. It takes a lot of time and cost to do wind tunnel test needed it, so numerical simulation approach instead of that is recommended sometimes. Simulating wind load in the time domain using known spectra data of fluctuating wind load is particularly useful for some prediction of windinduced vibration which is more or less narrow banded process such as across-wind response of a tall building. The simulation procedure is taken from Deodatis. In this study, fluctuating across-wind load acting on a tall building was simulated numerically in the time domain using the across-wind load spectra proposed by A.Kareem in1982. And using this simulated across-wind load estimated the reduced across-wind vibration response of a tall building using the linear quadratic Gaussian (LQG) control method.

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Sawicki, J. T., and W. K. Gawronski. "Balanced Model Reduction and Control of Rotor-Bearing Systems." Journal of Engineering for Gas Turbines and Power 119, no. 2 (April 1, 1997): 456–63. http://dx.doi.org/10.1115/1.2815596.

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An effective technique is applied to the suppression of vibrations in flexible rotor-bearing systems with small gyroscopic effects. A balanced linear-quadratic-Gaussian (LQG) controller design procedure is implemented. The size of the controller is reduced in two stages by using (i) a balanced model reduction, and (ii) an LQG balanced reduction. The condition for a gyroscopic matrix is developed that allows one to ignore the rotor gyroscopic effects in the process of the controller design, although they are included in the rotor dynamics. The approach is illustrated on a typical rotor-bearing system represented by a 48 degree-of-freedom finite element model.

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Essahafi, Mohamed, and Mustapha Ait Lafkih. "Microclimate control of a greenhouse by adaptive Generalized Linear Quadratic strategy." Indonesian Journal of Electrical Engineering and Computer Science 11, no. 1 (July 1, 2018): 377. http://dx.doi.org/10.11591/ijeecs.v11.i1.pp377-385.

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To highlight the conceptual aspects related to the implementation of techniques optimal control in the form state, we present in this paper, the identification and control of the temperature and humidity of the air inside a greenhouse. Using respectively an online identification based on the recursive least squares with forgotten Factor method and the multivariable adaptive linear quadratic Gaussian approach which the advanced technique (LQG) is presented. The design of this controller parameters is based on state models identified directly from measured greenhouse data. hence the performances of the controller developed are illustrated by different tests and simulations on identified models of a greenhouse. Discussions on the results obtained are then processed in the paper to show the effectiveness of the controller in terms of stability and optimization of the cost of control.

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32

Karim, Selam, Allaoui Tayeb, and Tadjine Mohamed. "LQG Controller for the Control of Active and Reactive Power of DFIG Operating Under Inter-turn Short Circuit Fault." Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 13, no. 3 (May 18, 2020): 340–47. http://dx.doi.org/10.2174/2352096511666181114120443.

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Objective: This article presents a comparative study between the direct control for a Doubly- Fed Induction Generator (DFIG) in the healthy and faulty mode. Methods: First with classical IP controller then Linear Quadratic Gaussian (LQG) controller which propose an ensemble of Linear Quadratic Regulator and Kalman filter for the state estimation. The developed model of the machine allows the simulation of the inter-turn short circuit in the stator. The use of the LQG method provides very good performance for motor operation and robustness of the control law despite the external perturbation. The performance of the control is compared to a classical controller's PI. Results: The obtained results demonstrate that this type of controller allows the alleviation of the mechanical stress and it ensures good performances under fault, the continuity of this system is ensured. Conclusion: The simulation has been carried out using a MATLAB script and the results are presented.

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33

Zhao, Yu Liang, and Zhao Dong Xu. "Elastic-Plastic Time History Analysis of MR Damping Structure Based on LQG Algorithm." Applied Mechanics and Materials 858 (November 2016): 145–50. http://dx.doi.org/10.4028/www.scientific.net/amm.858.145.

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This paper discussed an elastic-plastic time-history analysis on a structure with MR dampers based on member model, in which the elastoplastic member of the structure is assumed to be single component model and simulated by threefold line stiffness retrograde model. In order to obtain better control effect, Linear Quadratic Gaussian (LQG) control algorithm is used to calculate the optimal control force, and Hrovat boundary optimal control strategy is used to describe the adjustable damping force range of MR damper. The effectiveness of the MR damper based on LQG algorithm to control the response of the structure was investigated. The results from numerical simulations demonstrate that LQG algorithm can effectively improve the response of the structure against seismic excitations only with acceleration feedback.

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34

Chen, Z. H., and Y. Q. Ni. "Adaptive Semiactive Cable Vibration Control: A Frequency Domain Perspective." Shock and Vibration 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/2593503.

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An adaptive solution to semiactive control of cable vibration is formulated by extending the linear quadratic Gaussian (LQG) control from time domain to frequency domain. Frequency shaping is introduced via the frequency dependent weights in the cost function to address the control effectiveness and robustness. The Hilbert-Huang transform (HHT) technique is further synthesized for online tuning of the controller gain adaptively to track the cable vibration evolution, which also obviates the iterative optimal gain selection for the trade-off between control performance and energy in the conventional time domain LQG (T-LQG) control. The developed adaptive frequency-shaped LQG (AF-LQG) control is realized by collocated self-sensing magnetorheological (MR) dampers considering the nonlinear damper dynamics for force tracking control. Performance of the AF-LQG control is numerically validated on a bridge cable transversely attached with a self-sensing MR damper. The results demonstrate the adaptivity in gain tuning of the AF-LQG control to target for the dominant cable mode for vibration energy dissipation, as well as its enhanced control efficacy over the optimal passive MR damping control and the T-LQG control for different excitation modes and damper locations.

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35

Sohn, J. W., H. S. Kim, and S. B. Choi. "Active vibration control of smart hull structures using piezoelectric actuators." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 220, no. 9 (September 1, 2006): 1329–37. http://dx.doi.org/10.1243/09544062c06105.

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In this study, dynamic characteristics of an end-capped hull structure with surfacebonded piezoelectric actuators are studied and active vibration controller is designed to suppress the undesired vibration of the structure. Finite-element modelling is used to obtain practical governing equation of motion and boundary conditions of smart hull structure. A modal analysis is conducted to investigate the dynamic characteristics of the hull structure. Piezoelectric actuators are attached where the maximum control performance can be obtained. Active controller on the basis of a linear quadratic Gaussian (LQG) theory is designed to suppress the vibration of smart hull structure. It is observed that closed-loop damping can be improved with suitable weighting factors in the developed LQG controller and the structural vibration can be successfully suppressed.

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36

Plummer, A. R. "A comparison of linear discrete-time design methods for servosystem control." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 211, no. 4 (June 1, 1997): 281–300. http://dx.doi.org/10.1243/0959651971539812.

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Three linear discrete-time model-based controller design techniques are compared: pole placement, linear quadratic Gaussian (LQG) and H∞ control. It is shown that design choices can be made for all three controllers by considering the effect on the sensitivity functions of the closed-loop system. Also all three controllers can be implemented using an identical controller structure. A comparative study of the application of the techniques to an electromechanical servosystem is made. The controllers are designed from a discrete-time plant model estimated from experimental data, and a polynomial-based solution method is used in each case. It is concluded that acceptable performance can be achieved using any of the controllers if informed design choices are made.

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Li, Jin Hui, Jie He, and Xu Hong Li. "LQG Controller Design for Heavy Vehicle Active Suspension Based on OT-AHP Method." Applied Mechanics and Materials 509 (February 2014): 206–12. http://dx.doi.org/10.4028/www.scientific.net/amm.509.206.

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In order to develop more scientific LQG (Linear-Quadratic Gaussian) optimal controller of vehicle active suspension, based on vehicle systme dynamics and modern control theory, the LQG controller of one 4-dof active suspension vehicle model was presented. And the index weighting coefficiens in LQG controller were rationally determind by AHP (Analytic Hierarchy Process) method. Based on this, for furtherly improving vehicle performanc, the subjective important degrees in AHP method were optimized by OT (Othogonal Test) method which took the linear weighted sum of ride comfort and road friendliness index as the comprehensive performance evaluation index. The simulation results showed that, compared to AHP method, the LQG active suspension vehicle designed by OT-AHP (Orthogonal Test of Analytic Hierarchy Process) method could have better comprehensive performance, which could provide new ideas for the development of vehicle active suspension.

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Zhang, Lifu, Heng Zhang, Cunhua Li, and Buxi Ni. "Optimal Jamming Attack Scheduling in Networked Sensing and Control Systems." International Journal of Distributed Sensor Networks 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/206954.

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This paper investigates the optimal jamming attack scheduling in Networked Sensing and Control Systems (NSCS). From viewpoint of the attacker, we formulate an optimization problem which maximizes the Linear Quadratic Gaussian (LQG) control cost with attacking energy constraint in a finite time horizon. For two special cases, we obtain that the optimal jamming attack schedule is to consecutively attack in the given time horizon. For the general case, we propose an algorithm to find the optimal schedules. Finally, we study the effectiveness of our proposed attack strategies on our established semiphysical testbed.

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Gomonwattanapanich, O., N. Pannucharoenwong, P. Rattanadecho, S. Echaroj, and S. Hemathulin. "Vibration Control of Vehicle by Active Suspension with LQG Algorithm." International Journal of Automotive and Mechanical Engineering 17, no. 2 (July 11, 2020): 8011–18. http://dx.doi.org/10.15282/ijame.17.2.2020.19.0600.

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In this paper, the ride performance of a vehicle with active suspension and Linear Quadratic Gaussian (LQG) controller has been studied and is compared to the performances of a traditional passive suspension system. The study includes variables that are related to a passenger’s comfort: vertical position, vertical velocity, pitch angle, pitch velocity, roll angle, and roll velocity. The performances of the two systems are evaluated by maximum values and root mean square (RMS) of the variables when riding on a sinusoidal road profile. The simulation results show that the vehicle with active suspension and LQG controller performs better than passive suspension system where the maximum values decrease by 85.77%, 92.73%, 50.31% 86.83%, 89.41%, 43.28%, and RMS values decrease by 88.59%, 92.36%, 42.99%, 87.61%, 90.85%, and 42.79% for vertical position, vertical velocity, pitch angle, pitch velocity, roll angle, and roll velocity, respectively.

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Liu, Hua Chu. "Optimal Control of a Nuclear Reactor in Load Follow Based on LQG/LTR." Advanced Materials Research 591-593 (November 2012): 1563–66. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.1563.

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Load follow is necessary in the operation of a power plant due to the need of power changing with time. In the load following of a nuclear plant, many special factors have to be considered, which makes the control strategy particularly difficult as well as important. Among many strategies, Linear Quadratic Gaussian and Loop Transfer Recovery (LQG/LTR) design approach is an efficient method for L-F, and is applied to a model of a practical nuclear reactor. The simulation shows the robust control method LQG/LTR meet the control requirements of the neutron flux spatial distribution during load following. And a Kalman-filter based feedback control is also applied in this approach to eliminate the oscillations caused by Xenon poisoning within the nuclear reactor.

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41

Mahinzaeim, Mahyar. "A new method for proving the separation principle for the infinite-dimensional LQG regulator problem." IMA Journal of Mathematical Control and Information 36, no. 3 (March 21, 2018): 835–48. http://dx.doi.org/10.1093/imamci/dny008.

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Abstract This paper gives an alternative perspective on the standard linear quadratic Gaussian regulator problem for infinite-dimensional state-space systems. We will show that when considered on an extended Hilbert state-space, the originally stochastic control problem can be phrased as a deterministic one. In this setting we obtain a new method of proof for the well-known separation principle which does not involve probabilistic considerations.

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42

Ma, Shu Yuan, Bdran Sameh, Saifullah Samo, and Aymn Bary. "Improvement Shifting Control of Continuously Variable Transmission (CVT) by Using PID, Pole Placement and LQG." Applied Mechanics and Materials 446-447 (November 2013): 1165–70. http://dx.doi.org/10.4028/www.scientific.net/amm.446-447.1165.

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In this paper, the CVT shifting control system based on vehicle operating conditions is modeled and simulated using MATLAB/SIMULINK. The modeling stage begins with the derivation of required mathematical model to illustrate the CVT shifting control system. Then, Linear Quadratic Gaussian (LQG), Proportional- Integrated-Derivative (PID) and Pole Placement are applied for controlling the shifting speed ratio of the modeled CVT shifting system. Simulation results of shifting controllers are presented in time domain and the results obtained with LQG are compared with the results of PID and Pole placement technique. Finally, the performances of shifting speed ratio controller systems are analyzed in order to choose which control method offers the better performance with respect to the desired speed ratio. According to simulation results, the LQG controller delivers better performance than PID and Pole Placement controller.

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DONG, X. M., MIAO YU, S. L. HUANG, ZUSHU LI, and W. M. CHEN. "HALF CAR MAGNETORHEOLOGICAL SUSPENSION SYSTEM ACCOUNTING FOR NONLINEARITY AND TIME DELAY." International Journal of Modern Physics B 19, no. 07n09 (April 10, 2005): 1381–87. http://dx.doi.org/10.1142/s0217979205030335.

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MR suspension systems have significant non-linearity and time-delay characteristics. For this reason, linear feedback control of an MR suspension has limited vibration control performance. To address this problem, a four DOF half car suspension model with two MR dampers was adopted. Having analyzed non-linearity and time-delay of the MR suspension, a Human-Simulation Intelligent Control (HSIC) law with three levels was designed. Simulation verified effects of HSIC in solving the problem of non-linearity and time-delay of MR dampers. In comparison, simulation of linear-quadratic gaussian (LQG) without considering the non-linearity and time-delay of MR suspension is also made. The simulation results show that the HSIC controller is faster than LQG controller under bump input and has better stability and accuracy, and it can achieve smaller acceleration peak value and root mean square (RMS) and better ride comfort compared with LQG controller under random input.

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44

Sohn, Jung Woo, Heung Soo Kim, and Seung Bok Choi. "Dynamic Characteristics of Smart Hull Structures Featuring Piezoelectric Materials." Key Engineering Materials 306-308 (March 2006): 1145–50. http://dx.doi.org/10.4028/www.scientific.net/kem.306-308.1145.

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In this paper, dynamic characteristics of an end-capped hull structure with surface bonded piezoelectric actuators are studied. Finite element technique is used to ensure application to practical geometry and boundary conditions of smart hull structure. Modal analysis is conducted to investigate the dynamic characteristics of the hull structure. Piezoelectric self-sensing actuators are attached where the maximum control performance can be obtained. Active controller based on Linear Quadratic Gaussian (LQG) theory is designed to suppress vibration of smart hull structure. It is observed that closed loop damping can be improved with suitable weighting factors in the developed LQG controller.

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Shan, Xiaobiao, Henan Song, Chong Zhang, Guangyan Wang, and Jizhuang Fan. "Linear System Identification and Vibration Control of End-Effector for Industrial Robots." Applied Sciences 10, no. 23 (November 29, 2020): 8537. http://dx.doi.org/10.3390/app10238537.

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This paper presents the discrete state space mathematical model of the end-effector in industrial robots and designs the linear-quadratic-Gaussian controller, called LQG controller for short, to solve the low frequency vibration problem. Though simplifying the end-effector as the cantilever beam, this paper uses the subspace identification method to determine the output dynamic response data and establishes the state space model. Experimentally comparing the influences of different input excitation signals, Chirp sequences from 0 Hz to 100 Hz are used as the final estimation signal and the excitation signal. The LQG controller is designed and simulated to achieve the low frequency vibration suppression of the structure. The results show that the suppression system can effectively suppress the fundamental natural frequency and lower vibration of end-effector. The vibration suppression percentage is 95%, and the vibration amplitude is successfully reduced from ±20 μm to ±1 μm. The present work provides an effective method to suppress the low frequency vibration of the end-effector for industrial robots.

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46

Chen, Shinn-Horng, and Jyh-Horng Chou. "Linear Structure Vibration Control Using MFT and Robust Kalman-Filter-Based OMFC Method." Journal of Mechanics 15, no. 1 (March 1999): 1–9. http://dx.doi.org/10.1017/s1727719100000265.

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ABSTRACTThis paper proposes a robust Kalman-filter-based optimal model-following control (OMFC) methodology for actively suppressing the vibration of the mechanical structure system, which is modeled by the modal force technique (MFT) and subjects to both disturbance/noise uncertainties and linear structured time-varying parameter perturbations. The proposed method can not only avoid the problem of how to choose appropriate weighting matrices in the quadratic cost function of the linear quadratic Gaussian (LQG) control but also make the controlled closed-loop system to have desired system response characteristics. Besides, this paper also presents a robust stability criterion to guarantee that the designed controller can keep the controlled mechanical structure system from the possibility of time-varying-parameter-perturbation-induced instability. An example of L-shaped cantilever beam structure system is employed to demonstrate the application of the proposed method and the use of the robust stability criterion. Numerical simulation is performed to evaluate the improvement of the vibration response.

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Arantes, Gilberto, Luiz S. Martins-Filho, and Adrielle C. Santana. "Optimal On-Off Attitude Control for the Brazilian Multimission Platform Satellite." Mathematical Problems in Engineering 2009 (2009): 1–17. http://dx.doi.org/10.1155/2009/750945.

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This work deals with the analysis and design of a reaction thruster attitude control for the Brazilian Multimission platform satellite. The three-axis attitude control systems are activated in pulse mode. Consequently, a modulation of the torque command is compelling in order to avoid high nonlinear control action. This work considers the Pulse-Width Pulse-Frequency (PWPF) modulator which is composed of a Schmidt trigger, a first-order filter, and a feedback loop. PWPF modulator holds several advantages over classical bang-bang controllers such as close to linear operation, high accuracy, and reduced propellant consumption. The Linear Gaussian Quadratic (LQG) technique is used to synthesize the control law during stabilization mode and the modulator is used to modulate the continuous control signal to discrete one. Numerical simulations are used to analyze the performance of the attitude control. The LQG/PWPF approach achieves good stabilization-mode requirements as disturbances rejection and regulation performance.

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48

Duda, Zdzislaw. "State estimation in a decentralized discrete time LQG control for a multisensor system." Archives of Control Sciences 27, no. 1 (March 1, 2017): 29–39. http://dx.doi.org/10.1515/acsc-2017-0002.

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Abstract In the paper a state filtration in a decentralized discrete time Linear Quadratic Gaussian problem formulated for a multisensor system is considered. Local optimal control laws depend on global state estimates and are calculated by each node. In a classical centralized information pattern the global state estimators use measurements data from all nodes. In a decentralized system the global state estimates are computed at each node using local state estimates based on local measurements and values of previous controls, from other nodes. In the paper, contrary to this, the controls are not transmitted between nodes. It leads to nonconventional filtration because the controls from other nodes are treated as random variables for each node. The cost for the additional reduced transmission is an increased filter computation at each node.

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Sohn, Jung Woo, and Seung Bok Choi. "Active Vibration Control of Smart Hull Structure Using Piezoelectric Composite Actuators." Advanced Materials Research 47-50 (June 2008): 137–40. http://dx.doi.org/10.4028/www.scientific.net/amr.47-50.137.

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In this paper, active vibration control performance of the smart hull structure with Macro-Fiber Composite (MFC) is evaluated. The governing equations of motion of the hull structure with MFC actuators are derived based on the classical Donnell-Mushtari shell theory. Subsequently, modal characteristics are investigated and compared with the results obtained from finite element analysis and experiment. The governing equations of vibration control system are then established and expressed in the state space form. Linear Quadratic Gaussian (LQG) control algorithm is designed in order to effectively and actively control the imposed vibration. The controller is experimentally realized and control performances are evaluated.

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Li, Zheng Ying, Peng Peng Dang, and De Jian Mu. "MR Damper Semiactive Control for Bridge under Multi-Support Seismic Excitation." Applied Mechanics and Materials 90-93 (September 2011): 1402–5. http://dx.doi.org/10.4028/www.scientific.net/amm.90-93.1402.

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For vibration control of long-span arch bridges under multi-support seismic excitation, this paper presents schemes of control to seismic responses of arch bridges with Magneto-Rheological dampers(MRD). In the semi-active control system of arch bridge-MRD, Linear Quadratic Gaussian (LQG)-based Sign function control algorithm is used to command MRD，and traveling wave effects on the responses of structure are considered. The Nimu arch bridge is used as a simulation example to verify the proposed control scheme. Numerical results show that traveling wave effects have no unfavorable influence on the control to response of arch bridge.

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Journal articles on the topic 'Linear Quadratic Gaussian (LQG) control'

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