• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.1-7
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• 2007

Active magnetic bearing has been adopted to support the rotor by electomagnetic force without mechanical contact and lubrication process. A property of the control system for magnetic bearing is improved in accordance with making higher system gain. If the control system has integral part, an excessive overshoot response is shown by making higher integral gain. Therefore, this paper suggests a PID control system in order to eliminate the overshoot at the first stage and improve response characteristics to an impact disturbance at the status of levitation. The control gain was obtained by LQR design method which has the structure of I-PD control system in the state space. The PID control system containing prefilter has the same structure as the I-PD control system. Therefore, the PID control system adopted is able to be tuned by LQR design method. Finally, this paper shows the effect of the prefilter on the active magnetic bearing system through response experiments for levitation responses.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.132-138
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• 2011

This paper presents an intelligent control approach for lateral position control of an autonomous four wheel steered snowplowing robotic vehicle. The vehicle is built for removing snow on the highway. Dynamics of the vehicle is derived and linearized for LQR control. Lateral position is controlled by the LQR method first, then the neural network control technique is introduced to improve tracking performances under the presence of load. The feasibility of using four wheel steering control is investigated by simulation studies of lateral position tracking of the Ford F-250 truck model. Performances of a LQR control method and a neural network control method under virtual snowplowing situation are compared.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.190-196
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• 2014

In this paper, we get state equations based on wheel's rotation, tilt and steering are independent each other in balancing robot. Accordingly, we propose two LQR controllers which are appropriate for rotation and steering control of a balancing robot. And its superiority and appropriateness are demonstrated by a comparison to a PID method. Simulation results verify the possibility of upright balancing, rectilinear motion and position control. Moreover, experimental results show that it guarantees the performance to apply the two LQR controllers to balance the robot.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.46-49
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• 2002

This paper presents I-PD controller design using LQR method in a two-inerita motor system to satisfy the design specification in time domain. And to provide a systematic LQ analysis for two-inerita motor system. The tuning parameters of LQ(I-PD) controller are determinated by the relationships between the design parameters of the overshoot and the settling time which are design specifications in time domain, and the weighting factors Q and R in LQR we can achieve the performance-robustness in time domain as well as the stability-robustness.

• Journal of Energy Engineering
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• v.13 no.1
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• pp.68-74
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• 2004

This paper presents the design of DSTATCOM (Distribution Static Synchronous Compensator) controller. The results are verified by using PSCAD/EMTDC package. The state equation derived by decomposition analysis of DSTATCOM current component is applied to load model and the combined model which considered constraint condition. In case of single line to ground fault, the conventional method of Pl control is compared with LQR control technique. LQR control is shown to be superior in terms of response profile and composition of voltage sag.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.988-991
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• 1996

The purpose of this thesis is to develop methods of designing robust LQR/LQG controllers for time-varying systems with real parametric uncertainties. Controller design that meet desired performance and robust specifications is one of the most important unsolved problems in control engineering. We propose a new framework to solve these problems using Linear Matrix Inequalities (LMls) which have gained much attention in recent years, for their computational tractability and usefulness in control engineering. In Robust LQR case, the formulation of LMI based problem is straightforward and we can say that the obtained solution is the global optimum because the transformed problem is convex. In Robust LQG case, the formulation is difficult because the objective function and constraint are all nonlinear, therefore these are not treatable directly by LMI. We propose a sequential solving method which consist of a block-diagonal approach and a full-block approach. Block-diagonal approach gives a conservative solution and it is used as a initial guess for a full-block approach. In full-block approach two LMIs are solved sequentially in iterative manner. Because this algorithm must be solved iteratively, the obtained solution may not be globally optimal.

• 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.