• Journal of Advanced Marine Engineering and Technology
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• 제31권4호
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• pp.462-467
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• 2007

The design and synthesis of a state feedback controller assumes the feedback of all state variables of the system. However, some state variables are not physical quantifies so that sensors may not be available, or may be too expensive to measure. Hence, a state observer can be an alternative to estimate unmeasurable state variables. This paper therefore presents a scheme for state observer-based stabilization control of inverted pendulum systems. The feedback gain matrices of both the state feedback controller and the state observer are tuned by real-coded genetic algorithms(RCGAs) such that the given performance indices are minimized. The proposed method is demonstrated through simulations.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.705-707
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• 2018

Rotary Inverted Pendulum 은 제어분야에서 비선형 제어 시스템을 설명하기 위해 자주 사용되어왔다. 본 논문은 강화학습 에이전트의 환경으로써 Rotary Inverted Pendulum 을 도입하였다. 이를 통해서 강화학습이 실제 세계에서의 복합적인 문제를 해결할 수 있음을 보인다. 강화학습 에이전트의 가상 환경과 실제 환경을 맵핑시키기 위해서 Ethernet 연결 위에 MQTT 프로토콜을 사용하였으며 이를 통해서 경량화된 IoT 분야에서의 강화학습의 활용도를 조명한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.227-233
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• 1996

The Inverted Pendulum has been one of most popular nonlinear dynamic systems for the exploration of control techniques. This paper presents a new linear optimal control techniques and nonlinear neural network learning methods. The multiayered neural networks are used to add nonlinear effects on the linear optimal regulator(LQR). The new regulator can compensate nonlinear system uncertainties that are not considered in the LQR design, and can tolerated a wider range of uncertainties than the LQR alone. The new regulator has two neural networks for modeling and control. The neural network for modeling is used to obtain a more accurate model than the given mathematical equations. The neural network for control is used to overcome deficiencies by adding corrections to the linear coefficients of the LQR and by adding nonlinear effects on the LQR. Computer simulations are performed to show the applicability and a more robust regulator than the LQR alone.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2242-2244
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• 2003

This paper considers a networked control system (NCS) that consists of an inverted cart pendulum, a digital controller, and a controller area network (CAN) in which the actuator and sensors of the pendulum are connected to form a closed-loop system. The worst-case message response time (WCMRT) in the CAN is analyzed and the analysis results are applied to the target control system. For the case where the control system cannot satisfy the WCMRT condition and therefore time delays are inevitable, the Luck and Ray method is used to compensate the network-induced time delays. Simulations are carried out to show the feasibility of the proposed scheme.

• Journal of Mechanical Science and Technology
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• 제17권10호
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• pp.1466-1474
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• 2003

This paper presents a system modeling, controller design and implementation for a rotational inverted pendulum system (RIPS), which is an under-actuated system and has the problem of unattainable velocity state. Two control strategies are applied to the RIPS. One is a sliding mode control method using the parameterization of both the hyperplane and the compensator for output feedback. The other is the disturbance observer which estimates disturbance and some modeling errors of RIPS with less computational effort. Some simulations and various kinds of experiments are performed in order to verify that the proposed controller has the ability to control RIPS whose velocity is assumed to be unavailable. The results of the simulations and experiments show that the proposed control system has superior performance for disturbance rejection and regulation at certain initial conditions as well as the robustness to model uncertainties.

• 제어로봇시스템학회논문지
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• 제12권4호
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• pp.346-352
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• 2006

In a networked control system (NCS), time delays which are larger than one sampling period can change the control period. As a result, it may cause system instability. This paper presents a control method for an NCS using the controller area network (CAN), where time delays arise in the control loop. Specifically, a simple yet efficient method is proposed to improve control performance in the presence of time delays. The proposed method, which can be regarded as a gain scheduling method, selects a suitable LQ control gain among several gains to deal with the problems due to the change of control period. It is found that the gain can be scheduled in terms of the relation between the gain and the sampling period, which is represented by first-order algebraic equations. The proposed method is evaluated with an inverted cart pendulum system where the actuator and sensors are connected through the CAN. Experiment results are presented to show the efficiency of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.510-513
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• 2005

Due to the asymptotic property, deadbeat control can hardly be applied to the continuous time system control. But some delay element method can deal such a problem. Besides delay element method, well-known digital deadbeat control can be used by the aid of some smoothing elements. In this paper, 2nd order smoothing element is used for the smoothing of the digital deadbeat controller. And this element is argumented to the plant, and so control problem is to control the argumented system digitally. We simulated this control system using Matlab language and finally apply this algorithm to the rotary inverted pendulum system.

• 조명전기설비학회논문지
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• 제18권6호
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• pp.108-113
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• 2004

점근특성 때문에 deadbeat제어는 연속계시스템에는 거의 적용이 불가능하다. 그러나 지연요소법은 이런 문제를 해결할 수 있다. 지연요소법외에도 잘 알려진 디지털 deadbeat제어가 평활요소를 추가하여 사용될 수 있다. 본 논문에서는 2차 평활요소를 디지털 deadbeat제어기에 사용한다. 그리고 이 요소는 플랜트에 확장되고 따라서 확장된 시스템을 디지털제어하게 된다. 이 제어시스템을 Matlab언어를 사용하여 회전형 도립진자 시스템에 적용하여 시뮬레이션한다.

• 대한전기학회논문지:시스템및제어부문D
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• 제49권3호
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• pp.157-163
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• 2000

In this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algoithm(RVEGA) was presented for stabilization of an Inverter Pendulum(IP) system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the determinations of input or output neuron, the deleted neuron and the activation functions types are given according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. Through the simulations, we showed that the finally acquired optimal ENNC was successfully applied to the stabilization control of an IP system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1262-1266
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• 2003

Fuzzy sliding mode controller for a class of uncertain nonlinear dynamical systems is proposed and analyzed. The controller's construction and its analysis involve sliding modes. The proposed controller consists of two components. Sliding mode component is employed to eliminate the effects of disturbances, while a fuzzy model component equipped with an adaptation mechanism reduces modeling uncertainties by approximating model uncertainties. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum. The results show that both alleviation of chattering and performance are achieved.