• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.79-82
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• 1999

The right half plane (RHP) zeros may cause severe problems, such as undershoots, oscillations and time delay in the transient response of the systems. In this paper, we formulate a linear quadratic type problem to deal with the effects of the RHP zeros in the nonminimum phase systems. Based on the LQ formulation, this paper shows the trade-off relation between undershoot and rising time performances in nonminimum phase systems by using a new performance index which consists of new state and tracking error. And performances of the proposed method are shown via computer simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.311-316
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• 1994

In this study, a governing equation for 4-axis active magnetic bearing system composed of a rigid rotor and two radial magnetic bearings is derived. We find out that there are two kind of coupling between control axes in the system. And digital contralized controller is designed based on state-space approach and linear quadratic regulator(LQR) theory. By numerical simulation, it is shown what the designed controller can stabilize the system and control the coupling effectively using limited control input.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.520-523
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• 2004

A phase-locked loop control system designed by using the linear quadratic regulator approach is presented in this paper. The system thus designed is optimal system when system is in locked state and the parameter value of loop filter which is an active PI filter can be obtained easily. By considering the structure of loop filter of phase-locked loop is included in the process to be controlled, a type 1 servo system can be constructed when voltage control oscillator is considered as an integrator. The integral gain of the proposed system obtained by linear quadratic regulator approach can be used as an optimal value to design the parameter of loop filter. The implemented result in controlling the second-order lag pressure process by using the proposed scheme show that the system response is fast with no overshoot and no steady-state error. Furthermore, the experimental results are also shown in term of output disturbance effect rejection, tracking and process parameter changed.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.99-107
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• 2003

In a winding process, important control specifications include regulation of web tension and velocity. In this research, an adaptive controller has been developed for controlling web tension and velocity in winding processes. For the controller design, the linear quadratic regulator theory has been adopted and a gain-scheduling scheme has been incorporated. A prototype winding system has been constructed, and the controller has been implemented in a real-time PC-based environment. The performance of the closed loop system has been evaluated via simulation and experiments, and it was observed that both the web tension and velocity could be regulated within a small tolerance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.71-76
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• 2008

This paper is concerned with the active vibration control of elevator by means of the active roller guide. To this end, a dynamic model for the horizontal vibration of the elevator consisting of a supporting frame, cage and active roller guides was derived using the energy method. Free vibration analysis was then carried out based on the equations of motion. Active vibration controller was designed based on the equations of motion using the LQR theory and applied to the numerical model. Rail irregularity and wind pressure variation were considered as external disturbance in the numerical simulations. The numerical results show that the active vibration control of elevator is possible.

• Journal of the Korean Institute of Navigation
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• v.23 no.3
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.14-25
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• 2012

Recently, the application and installation of the pod propeller to the cruise ship is dramatically increased. It is because pod propulsion system allows a lot of flexibility in design of the internal arrangement of a ship. To reflect this trend, many researches have conducted to use the pod propeller for the roll stabilization of a ship. In the paper, a roll stabilization controller is designed by using fins and pod propellers as the control actuators for cruise ships. Two kinds of control algorithms are adopted for the roll control system; LQR (Linear Quadratic Regulator) algorithm and frequency-weighted LQR algorithm. Through the numerical simulation, the effect of the turning rate of the pod propeller on the roll control system is analyzed. Analysis of the simulation results indicated that the turning rate of the pod propellers is one of the important parameters which give the significant effects on the roll stabilization.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.308-313
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• 2022

This paper proposes a velocity control method for a permanent magnet synchronous motor (PMSM) based on the Koopman operator that does not require model parameter information except for pole-pair of the motor and external load. First, the Koopman operator is derived using observable functions and observation data. Then, the desired q-axis current corresponding to the desired velocity is generated using the relationship between the continuous-time Koopman operator and the dynamics of PMSM. Also, the dynamic equation of PMSM is expressed as a linear form in observable space using the discrete-time Koopman operator. Finally, it is applied to the linear quadratic regulator (LQR) to derive the final form of control input. To verify the proposed method, the conventional cascade PI controller and the LQR controller configured with the existing technique are compared with the proposed method in the viewpoint of q-axis current generation and velocity tracking performance in an environment with noise and external load.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.660-664
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• 2003

The optimal thickness distribution of an active damping layer is sought so that it satisfies a certain constraint on the dynamic performance of a system minimizing control efforts. To obtain a topologically optimized configuration, which includes size and shape optimization, thickness of the active damping layer is interpolated using linear functions. With the control energy as the objective function to be minimized, the state error energy is introduced as the dynamic performance criterion for the system and used lot a constraint. The optimal control gains are evaluated from LQR simultaneously as the optimization of the layer position proceeds. From numerical simulation, the topologically optimized distribution of the active damping layer shows the same dynamic performance and cost as the Idly covered counterpart, which is optimized only in terms of control gains, with less amount of the layer.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.111-117
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• 2003

The Taylor model concept is introduced to design a controller with input and output data only. The parameters in Taylor model can be estimated using the input and output data and a controller can be designed based on Taylor model. The accuracy of Taylor model approximation can be improved by increasing the observation window and the order of Taylor model. The LQR method is applied to Taylor model to design power system stabilizers (PSS), and compared with the conventional PSS.