• 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.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2239-2241
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• 2004

이 논문은 최적 제어 설계방법 중 하나인 LQR 제어기의 과도 상태를 개선하는 방법에 관한 연구이다. 적절한 상태가중행렬과 제어가중행렬을 설정한 후 대수 Riccati 방정식을 풀면 LQR 제어기가 설계된다. 그런데 이 가중행렬은 시행착오 방법을 이용하여 설정하기 때문에 설계된 제어기의 과도 상태를 개선하기 하기가 매우 어렵다. 이러한 문제점을 해결하기 위한 방법으로 closed-loop 근과 가중행렬과의 상관관계를 수학적으로 표현하고, 이를 바탕으로 설계조건을 만족하도록 시스템의 근을 이동시키는 가중행렬을 구하는 방법을 제시한다. 원운동형 도립진자(rotary type inverted pendulum)를 통해 matlab 모의실험으로 그 타당성을 검증한다. 얻어진 결과를 이용하면 원하는 극점을 갖는 LQR 제어기를 체계적으로 설계할 수 있다.

• 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.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1105-1110
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• 2008

In this paper, a saturated LQR controller considering control input's saturation for stable linear time-invariant systems with single control input is studied. Based on Lyapunov stability, two linear matrix inequality sufficient existence conditions for this controller are presented. Through numerical simulations for 2DOF vibrating system, it is confirmed that the saturated LQR controller is stable in the presence of control input's saturation and it is also shown that this controller can be applied to vibrating system practically.

• 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.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.6
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• pp.49-53
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• 2002

This paper provides the systematic procedure to determine the weighting matrices of optimal controllers considering structural energy. Optimal controllers consist of LQR and ILQR. The weighting matrices are needed first in the conventional optimal control design strategy. However, they are in general dependent on the experienced knowledge of control designers. Applying the Lyapunov function to total structural energy and using the condition that its derivative is negative, we can determine the weighting matrices without difficulty. It is proven that the control efficiency with using determined weighting matrices is achieved well for LQR and ILQR controllers.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.6
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• pp.505-511
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• 2015

Solid oxide fuel cell operate at high temperature ($800{\sim}1000^{\circ}C$). High temperature have an advantage of system efficiency, but a weak durability. In this study, linear state space controller is designed to handle the temperature of solid oxide fuel cell system for proper thermal management. System model is developed under simulink environment with Thermolib$^{(R)}$. Since the thermally optimal system integration improves efficiency, very complicated thermal integration approach is selected for system integration. It shows that temperature response of fuel cell stack and catalytic burner are operated at severe non-linearity. To control non-linear temperature response of SOFC system, gain scheduled linear quadratic regulator is designed. Results shows that the temperature response of stack and catalytic burner follows the command over whole ranges of operations.

• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.2
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• pp.118-128
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• 2012

The goal of this paper is to design the target tracking controller for a quadrotor micro UAV using a vision sensor. First of all, the mathematical model of the quadrotor was estimated through the Prediction Error Method(PEM) using experimental input/output flight data, and then the estimated model was validated via the comparison with new experimental flight data. Next, the target tracking controller was designed using LQR(Linear Quadratic Regulator) method based on the estimated model. The relative distance between an object and the quadrotor was obtained by a vision sensor, and the altitude was obtained by a ultra sonic sensor. Finally, the performance of the designed target tracking controller was evaluated through flight tests.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.