• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.2
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• pp.1-8
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• 2004

This paper presents an optimal robust LQ-PID controller design method for the second order system with time-delay to meet design specifications. By LQR formulation of the second order system with time-delay, the tuning parameters of PID controller are related by weighting factors Q and R of cost function. The selection of weighting factors Q and R are chosen to satisfy such the design specifications as overshoot and settling time.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2171-2175
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• 2002

Helicopter dynamics are plenty of nonlinearity. A complete mathematical model including propeller dynamics and fortes generated by the propellers is very difficult to obtain. So the method used to design to design a controller is a parameter estimation. Design controller based on variable structure system. This paper deals with LQR control technique to control efficiently, its elevation angle and azimuth one. The purpose of the experiment is to design a controller allows to use a desired elevation angle and azimuth ones. The system model has a helicopter model with 2-degree-of freedom. The simulation results were verified usefulness of controller.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2240-2242
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• 2001

A rotary double inverted pendulum, the nonlinear system has a regulation problem. In this paper, we linearize the nonlinear system at the upright equilibrium position. The linearized system can be expressed in state space. To maintain the upright position, we design a feedback controller using LQR(Linear Quadratic Regulator) algorithm. Then we simulate the system with third-order Adams Bashforth Moulton Method. The simulated result shows that the applied algorithm is effective for the regulation problem.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2170-2172
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• 2003

This paper presents the position tracking control of an inverted pendulum on an inclined railway. In general, inclining the railway leads to errors in the pendulum angle even though the pendulum is stabilized, which results in errors in the cart position. To solve this problem, a linear quadratic regulation (LQR) controller with an integrator is used for compensating the resulting error in the cart position. The proposed method is evaluated by comparing LQR controllers with and without an integrator. Experimental results show that the LQR controller with an integrator is better in performance than one without an integrator.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1867-1870
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• 1997

Waypoint guidance is a technique used to steer an autonomous vehicle along a desired trajectory. In this paper, a waypoint guidance algorithm for horizontal plane is derived by combining a line following guidance law and a turning guidance law. The line following guidance is derived based on LQR while the turning guidance is designed using rendzvous problem. Through simulation, the proposed method shows a good performance.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.380-385
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• 1996

The genetic algorithm(GA) is applied to the design of the nuclear power control system. The reactor control system model is described in the LQR configuration. The LQR system order is increased to make the tracking system. The key parameters of the design are weighting matrices, and these are usually determined through numerous simulations in the conventional design. To determine the more objective and optimal weightings, the improved GA is applied. The results show that the weightings determined by the GA yield the better system responses than those obtained by tile conventional design method.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1136-1141
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• 2004

This paper presents a control method for time-delay systems and verifies the performance of the designed control system via real experiments. Specifically, the control method is applied to a flexible-link system with time delays. The method combines time- and frequency-domain controllers: linear quadratic optimal controller (or LQR) and lag compensator. The LQR is used to stabilize the system in optimal fashion, whereas the lag compensator is used to compensate time-delay effects by increasing the delay margin of the system. With this methodology, the maximum allowable time delay can be increased significantly. The proposed method is simple but quite practical for time-delay system control as it is based on the conventional loop-shaping method, which gives practical insights on delay-phase relationship. Simulation and experiment results show that the method presented in this paper is feasible and practical.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.749-757
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• 2021

In transportation missions using quadrotor, the payload may change the model parameters, such as mass, moment of inertia, and center of gravity. Moreover, if position of the payload is constantly changing during flight, the effect can adversely affect the control performances. To handle this issue, we suggest Model Reference Adaptive Control based on Linear Quadratic Regulator(LQR+MRAC) to compensate the uncertainty caused by payload. Firstly, the mathematical modeling with the fixed payload is derived. Second, Linear Quadratic Regulator (LQR) is used to design the reference model and baseline controller. Also, through the Stability method, Adaptive law is derived to estimate the model parameters. To verify the performance of proposed control scheme, we compared LQR and LQR+MRAC in situations where uncertainties exist. And, when the disturbance exist, the classic MRAC and proposed controller is compared to analyze the transient response and robustness.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.2
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• pp.217-223
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• 1991

Most common applications of neural networks to control problems are the automatic motor controls using the artificial perceptual function. These control mechanisms are similar to those of the intelligent and pattern recognition control of an adaptive method frequently performed by the animate nature. In this paper, the pole-balancing problem is selected as the control object and an actual cart-pole controller is implemented by a computer interfacing and demonstrated as motor control using the reinforcement learning rule. In the experiment, given a change of the main parameters of cart-pole dynamics, a comparison is made between the LQR scheme and neural network method. The neural network method exhibits a more effecftive control action in a real situation having a large uncertainty than the LQR scheme.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.186-189
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• 2003

This paper presents an optimal tuning method of the decentralized PI controller of two-input, two-output(TITO) second order system to be formulated as LQR. The tuning method of proposed decentralized PI controller is developed by establishing the relationships between the closed-loop state equation including decentralized PI control factors and the closed-loop state equation of LQR, which can be guaranteed the performance and stability-robustness by selecting the weighting factors Q and R of the cost function in order to satisfy design specifications in frequency domain.