• 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.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.37-42
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• 2004

This paper presents an optimal and robust tuning method of decentralized PI controller for the TITO second order systems to be formulated as LQR. The procedure is developed by establishing relationships between the closed-loop state equation including the decentralized PI tuning parameter and the . closed-loop state equation of LQR and by selecting the weighting factors Q and R of the cost function in order to satisfy the design specifications In frequency domain which the stability robustness and satisfied the performance guaranteed.

• 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 KIEE Conference
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• 2007.07a
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• pp.306-307
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• 2007

본 논문은 계층적 공정 경쟁 유전자 알고리즘(Hierarchical Fair Competition-based Genetic Algorithms : HFCGA)을 이용하여 회전형 역 진자 시스템의 최적 Fuzzy 제어기 설계를 제안한다. 탐색 공간이 크거나 복잡한 최적해 탐색문제에 대해 조기 수렴 문제를 내제하고 있는 기존의 유전자 알고리즘의 해결방안으로 병렬 유전자 알고리즘이 개발되었으며, HFCGA는 병렬 유전자 알고리즘의 한 구조이다. 본 논문에서는 회전형 역 진자 시스템에 대해 LQR 제어기와 유사한 형태의 Fuzzy 제어기를 구성하고, HFCGA를 이용하여 최적의 제어기 파라미터들을 구한다. 그리고 시뮬레이션 및 실제 공정에 적용하여 LQR 제어기와 설계된 제어기의 성능을 평가한다.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.57.1-57
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• 2001

The objectives of congestion control in ATM (Asynchronous Transfer Mode) networks are maximum utilization of network resources, acceptable level of low cell loss and fairness among all VCs (Virtual Connections). In this paper, we present a congestion control algorithm which is based on state space model, The proposed controller uses optimal control algorithms (LQR, Mixed-LQR), where control parameters can be designed to ensure the stability of the control loop in a control theoretic sense, over the propagation delay. We show how the control mechanism can be used to design a controller to support ABR service based on feedback of explicit rates. Simulation results are presented to substantiate our claim.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.429-434
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• 1998

The previously developed control design methodology, EALQR(Eigenstructure Assignment/LQR), has better performance than that of conventional LQR or eigen-structure assignment. But it has a constraint for the weigting matrix in LQR, that is the weighting matrix could be indefinite for high-order systems. In this paper, the effects of the indefinite weighting matrix in EALQR on the Sequency domain properties are analyzed. The robustness criterion and quantitative frequency domain properties are also presented. Finally, the frequency do-main properties of EALQR has been analyzed by applying to a flight control system design example.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.4-41
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• 2001

In this paper, we propose a LQR(Linear Quadratic Regulator) controller design for the active suspension using two-degree-of-freedom quarter-car model. We can improve the inherent suspension problem, the tradeoff between ride quality and suspension travel by selecting appropriate weights in the LQR-objective function. Because any definite rules for selecting weights do not exist, we replace the designer´s trial and error with the optimization-algorithm, ES(Evolution Strategy). Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle´s state variables.

• 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.