• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.268-274
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• 2013

Any new method for controlling a nonlinear system has widely been reported. An inverted pendulum system has typically been used as a target system for demonstrating its usefulness. In this paper, we propose an algorithm to control a flexible joint cart based inverted pendulum system. Two carts are connected with a spring and one is a driving cart and the other is no driving cart with a pole. We here present a system modeling and a good fuzzy logic based control algorithm. We also introduce LQR (Linar Quadratic Regulator) technique for reducing the number of control variables. By using this technique, the number of input variables for a fuzzy logic controller is become only two not six. So the computational complexity is largely reduced. Moreover, a two-input fuzzy logic controller has a control rule table with a skew-symmetric property. And it will lead the design of a single-input fuzzy logic controller. In order to demonstrate the usefulness of the proposed method and prove the superiority of the proposed method, some computer simulations are presented.

• 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 Sensor Science and Technology
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• v.27 no.3
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• pp.165-169
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• 2018

A single-axis Cubli frame realized simply with an IMU sensor and DC motor is presented herein. To maintain the balance on the Cubli frame, an LQR controller based on a Lagrangian derivation of the dynamics was designed, which utilized the state variables of the frame angle and its angular acceleration, as well as the wheel angle and its angular acceleration. The designed LQR controller showed a settling time balancing capability of approximately two seconds and 40% of the maximum overshoot in Matlab/Simulink simulations. Our experimental results of the fabricated Cubli frame matched with the simulation results. It maintained balancing at the reference position even though an initial offset as well as external disturbance during the balancing was applied.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.70-71
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• 2007

This paper presents an application of LQR(Linear Quadratic Regulator) for experimental control moment gyroscope. To be specific, mathematical model is first derived based on the quaternion and Lagrange's equation, state feedback controller using LQR scheme is designed, and to show the stability of the scheme, experimental results are given.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.89-98
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• 2017

The control moment gyroscope(CMG) can be used for essential balancing control of a one-wheeled mobile robot. A single-gimbal CMG has a simple structure and can supply strong restoring torque against external disturbances. However, the CMG generates unwanted directional torque also besides the restoring torque; the unwanted directional torque causes instability in the one-wheeled robot control system that has high rotational degrees of freedom. This study proposes a control system for a one-wheeled mobile robot by using a CMG scissored pair to eliminate the unwanted directional torque. The well-known LQR control algorithm is designed for robustness against modeling error in the dynamic motion equations of a one-wheeled robot. Computer simulations for 3D nonlinear dynamic equations are carried out to verify the proposed control system with the CMG scissored pair and the LQR control algorithms.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1996.05a
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• pp.29-37
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• 1996

항공기 가스터빈 엔진은 폭넓은 운용 영역에서 다양한 임무 수행을 하도록 요구되어짐에 따라 항공기 전체의 성능과 직관되는 엔진의 성능에 대한 정밀한 동적 모사와 제어는 매우 중요하다. 본 연구에서는 대표적인 동적 모사 프로그램인 DYNGEN을 이용하여 비선형 동적 모사를 하였고, 이를 바탕으로 엔진의 제어를 위해 비선형 엔진에 대한 Piecewise 선형화를 통해 선형 동적 모사를 수행하였으며, 엔진의 최적 제어 기법으로 LQR 방법을 이용하여 성능 제어를 수행하였다.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.419-426
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• 2003

An efficient procedure using LQR method for determining optimal sliding surfaces appropriate for different controller types is provided. The parametric evaluation of the dynamic characteristics of sliding surfaces is peformed in terms of SMC controller performance of single-degree-of-freedom(SDOF) systems. The control force limit is considered in this procedure. Numerical simulations for multi-degree-of-freedom(MDOF) systems verify the effectiveness of proposed method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1330-1337
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• 2004

In this study, the equations of motion of a rigid rotor supported by magnetic bearings are derived via Hamilton's principle, and transformed to a state-space form for control purpose. The optimal motion control of rotor magnetic bearing system based on the LQR(linear quadratic regulator) theory is addressed. New schemes related to the selection of the state weighting matrix Q and the control weighting matrix R involved in the quadratic functional to be minimized are proposed. And the robust control of the system with an LMI(linear matrix inequality) based H$_{\infty}$ theory is dealt with in this paper. Loop shapings of TFM (transfer function matrix) are used to increase the performance of control capability of the system. The control abilities of LQR and H$_{\infty}$ controller are compared by simulation and experimental tests and show that the capability of H$_{\infty}$ controller is superior to that of LQR.