• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1201-1207
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• 2010

This paper shows to stabilize a balancing robot. We derive the dynamics of a balancing robot and design its controller using LQR method. For stabilizing balancing robot, we introduce a method to detect an angle using inertial sensors. In this study, we use a complementary filter to fuse signals by frequency response of gyroscope and accelerometer in order to measure the inclined angle of balancing robot. The filter coefficients are obtained by least square to minimize error in angle-detecting filter design. And then, after we derive a dynamics of balancing robot using Lagrange method, we linearize that dynamics for using LQR method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.701-705
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• 2014

This article presents a comparison among several yaw and roll motion controllers for vehicle rollover prevention. In the previous research, yaw and roll motion controllers can be independently designed for rollover prevention. Following this idea, several yaw and roll motion controllers are designed and compared in terms of rollover prevention. For the yaw motion control, PID, LQR, SMC (Sliding Mode Control) and TDC (Time-Delay Control) are adopted. For the roll motion control, LQR, LQ SOF (Static Output Feedback) control, PID, and SMC are adopted. To compare the performance of each controller, simulation is performed on a vehicle simulation package, CarSim$^{(R)}$. From simulation, TDC and LQ SOF are the best for yaw and roll motion control, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.16-22
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• 2016

The research on two-wheeled inverted pendulum (TWIP) mobile robots has been ongoing in a number of robotic laboratories around the world. In this paper, we consider a robust controller design for the TWIP mobile robot driving on uniform slopes. We use a 2 degree-of-freedom (DOF) model which is obtained by restricting the spinning motion in a 3 DOF motion dynamic equation. In order to design the robust controller guaranteeing stability of the TWIP mobile robot driving on inclined surface, we propose a sliding mode control based on the theory of variable structure systems and design a sliding surface using the theory of the linear quadratic regulation (LQR). For simulation, the dynamic model of the TWIP mobile robot is constructed using Mathworks' Simulink and the sliding mode control is also implemented using Simulink. From simulation results, we show that the proposed controller effectively controls the TWIP mobile robot driving on slopes.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.5
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• pp.352-360
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• 2010

This paper proposes a precise position control of an automatic door using a disturbance observer. Although the conventional PID controller is usually used for an automatic door system, the demand of the robust controller considering the parameter deviations and disturbances is increasing due to the various size and weight of a door. The linear model for an automatic door system is presented. Based on this model, the LQR controller using a state feedback controller and an observer are suggested. A disturbance observer to compensate the undesirable factors is also proposed. Simulation and Experimental results are presented to illustrate the feasibility of the proposed control strategy.

• 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 Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.461-470
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• 2003

This paper discusses a time domain controller, LQR, and a frequency domain controller, H₂, for optimal control of civil structures under seismic loads. Numerical simulations are performed on a three-story structure with Active Mass Driver (AMD), which is experimentally identified. Control effectiveness of each controller for the suppression of third floor acceleration responses is investigated when the similar maximum control force is used. Simulation results indicate that LQR is effective for acceleration response reduction while H₂ controller is efficient for utilizing control force.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.79-81
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• 2004

LQ-Servo controller inherits the stability-robustness from rational LQR structure and also, satisfies performance-robustness that is lacking in LQR structure by importing partial output feedback. In this paper, LQ-Servo controller is suggested for strengthening the performance-robustness. For this, Several executings are effectively performed by implementing to the rotational inverted pendulum system.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.236-242
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• 2008

In this paper, we propose an optimized fuzzy controller based on Hierarchical Fair Competition-based Genetic Algorithms (HFCGA) for rotary inverted pendulum system. We adopt fuzzy controller to control the rotary inverted pendulum and the fuzzy rules of the fuzzy controller are designed based on the design methodology of Linear Quadratic Regulator (LQR) controller. Simple Genetic Algorithms (SGAs) is well known as optimization algorithms supporting search of a global character. There is a long list of successful usages of GAs reported in different application domains. It should be stressed, however, that GAs could still get trapped in a sub-optimal regions of the search space due to premature convergence. Accordingly the parallel genetic algorithm was developed to eliminate an effect of premature convergence. In particular, as one of diverse types of the PGA, HFCGA has emerged as an effective optimization mechanism for dealing with very large search space. We use HFCGA to optimize the parameter of the fuzzy controller. A comparative analysis between the simulation and the practical experiment demonstrates that the proposed HFCGA based fuzzy controller leads to superb performance in comparison with the conventional LQR controller as well as SGAs based fuzzy controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.125-128
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• 2004

Q-learning은 강화학습의 한 방법으로서, 여러 분야에 널리 응용되고 있는 기법이다. 최근에는 Linear Quadratic Regulation (이하 LQR) 문제에 성공적으로 적용된 바 있다. 특히 시스템 모델의 파라미터에 대한 구체적인 정보가 없는 상태에서 적절한 입력과 출력만을 가지고, 학습을 통해 문제를 해결할 수 있어서 상황에 따라서 매우 실용적인 대안이 될 수 있다. 이에 따라 본 논문에서는 이러한 일반적인 LQR Q-learning(이하 LQRQL) 학습방법에 퍼지 모델을 이용하여 제어기를 설계하는 방법을 고려하고, 일반적인 LQROL 기법과 본 논문에서 제시한 방법의 결과를 비교하여 응용 가능성을 살펴보았다.