• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.461-470
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• 2003

This paper discusses a time domain controller, LQR, and a frequency domain controller, H₂, for optimal control of civil structures under seismic loads. Numerical simulations are performed on a three-story structure with Active Mass Driver (AMD), which is experimentally identified. Control effectiveness of each controller for the suppression of third floor acceleration responses is investigated when the similar maximum control force is used. Simulation results indicate that LQR is effective for acceleration response reduction while H₂ controller is efficient for utilizing control force.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.865-874
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• 2019

A controller for an underwater glider is presented. Considered underwater glider is a torpedo-shaped autonomous underwater vehicle installing adjustable buoyancy bag and movable battery in it. The controller is composed of an LQR controller to maintain zigzag vertical movement for gliding and two PD controllers to control elevator/rudder angles. The LQR controller controls the pumping speed into the buoyancy bag and the moving speed to locate the battery. One of the PD controller controls the elevator angle to assist the LQR controller, and the other controls the rudder angle to adjust the direction of the underwater glider. A reduced order Luenberger observer is adopted to estimates the center of gravity of the glider and the buoyancy mass that are essential but cannot be measured. Mathematical simulation using Matlab proved the validity of the proposed controller to obtain better performance than conventional LQR only controller under the influence of sea current.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.5
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• pp.78-84
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• 2001

The translation system is made up of springs, masses and a dashpot. This precise piece of equipment is controlled electro-mechanically by a motor and operating program. The control strategy of the system can be changed by spring stiffness, change of mass, and the damping coefficient of the dashpot. This system proves the necessity and effect of a closed loop control. In this paper, PD control experiments were implemented for the translation system. When the north falter was added on the PD controller, we compared the response characteristics of the two systems. The state feedback controller minimized scalar control gains and the resulting response characteristics of the system were studied using the LQR design. Finally, we improved the response characteristics of the translation system which are rising time, settling time, steady state error, and overshoot LQR was better as compared with PD control.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.574-580
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• 2007

This paper deals with LQR controller design method tor system having complex poles. The proposed method is capable of systematically calculating weighting matrices based on the pole's moving-range and the relational equation between closed-loop pole(s) and weighting matrices. The method moves complex poles to complex poles or two distinct real poles. This will provide much-needed functionality to apply LQR controller. The example shows the feasibility of the proposed method.

• Journal of Power Electronics
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• v.13 no.6
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• pp.1024-1031
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• 2013

This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbines, a set of operating conditions is identified and then a LQR controller is designed for each of the operating points. The feedback controller gains are then interpolated linearly to get a control law for the entire operating region. In addition, the aerodynamic torque and effective wind speed are estimated online to get the gain-scheduling variable for implementing the controller. The potential of this method is verified through simulation with the help of MATLAB/Simulink and GH Bladed. The performance and mechanical load when using LQR are also compared with those obtained when using a PI controller.

• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.68-77
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• 1997

The reactor power control system is described in the fashion of the order increased LQR system. To obtain the optimal state feedback gain vectors, the weighting matrix of the performance function should be determined. Since the contentional method has some limitations, stochastic searching methods are investigated to optimize the LQR weighting matrix using the modified genetic algorithm combined with the simulated annealing, a new optimizing tool named the hybrid MGA-SA is developed to determine the weighting parameters of the LQR system. This optimizing tool provides a more systematic approach in designing the LQR system. Since it can be easily incorporated with any forms of the cost function, it also provides the great flexibility in the optimization problems.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.108-120
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• 1998

In this paper, a new control system design algorithm, which has the advantages of the existing LQR and eigenstrcture assignment methods, is proposed. The method of the transformation matrix via block controller is utilized to develop the scheme. Using the proposed algorithm, LQR weighting matrices q and R, which satisfy the desired closed-loop eigenvalues and eigenvectors, can be achieved using only simple matrix computations. The usefulness of the proposed scheme is verified by applying to a numerical example and an automotive active suspension control system design.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2365-2370
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• 2008

In this paper, applications of wavelet neural network controller to position control of nonlinear system are considered. Wavelet neural network is used in the objectives which improve the efficiency of LQR controllers. It is possible to make unstable nonlinear systems stable by using LQR(Linear Quadratic Regulator) technique. And, in order to be adapted to disturbance effectively in this system it uses wavelet neural network controller. Applying this method to the position control of nonlinear system, its usefulness is verified from the results of experiment.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.79-83
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• 2000

Although it is well known that fuzzy learning controller is powerful for nonlinear systems, it is very difficult to apply a learning method if they are unstable. An unstable system diverges for impulse input. This divergence makes it difficult to learn the rules unless we can find the initial rules to make the system table prior to learning. Therefore, we introduced LQR(Linear Quadratic Regulator) technique to stabilize the system. It is a state feedback control to move unstable poles of a linear system to stable ones. But, if the system is nonlinear or complicated to get a liner model, we cannot expect good results with only LQR. In this paper, we propose that the LQR law is derived from a roughly approximated linear model, and next the fuzzy controller is tuned by the adaptive on-line learning with the real nonlinear plant. This hybrid controller of LQR and fuzzy learning was superior to the LQR of a linearized model in unstable nonlinear systems.

• Journal of IKEEE
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• v.5 no.2 s.9
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• pp.146-152
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• 2001

Two control techniques - PI and LQR(Linear Quadratic Regulator) - of DSTATCOM (Distribution Static Synchronous Compensator) for line voltage regulation in distribution system are presented. It is shown that the voltage waveform is improved if the proposed methods are applied in IEEE 13 radial distribution system using PSCAD/EMTDC package in case of single line-to-ground fault. The three cases - without control, with PI control and with LQR control - are compared. The LQR control is shown to be best in respect of response profile and control effort required among them.