• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.162-165
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• 1996

In this paper, we proposed an optimization method of the membership function and the numbers of fuzzy rule base for the stabilization controller of the inverted pendulum system by genetic algorithm(GAs). Conventional methods to these problems need to an expert knowledge or human experience. The proposed genetic algorithm method will tune automatically the input-output membership parameters and will optimize their rule-base.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.645-647
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• 1998

A position control algorithm for a inverted pendulum is studied. The proposed algorithm is based on a fuzzy theory and a steady state genetic algorithm(SSGA). The conventional fuzzy methods need expert's knowledges or human experiences. The SSGA, which is a optimization algorithm, tunes the input-output membership parameters and fuzzy rules automatically. The computer simulation to control a inverted pendulum is presented to illustrate the approaches.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.379-383
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• 1998

본 논문에서는 플랜트를 제어하는데 있어 광범위하게 사용되는 PD제어기의 파라미터를 결정하는 문제에 대한 연구를 하였다. 파라미터 결정 방법으로는 최근 최적화 문제에 많이 적용되고 있는 새로운 방법인 유전자 알고리즘을 사용하였다. 또한 이렇게 정해진 파라미터를 사용하여 이를 도립진자(Inverted Pendulum)에 적용하였고 도립진자의 응답특성을 분석, 고찰함으로써 PD제어기의 성능을 평가.확인하고 이 문제에 적용된 유전자 알고리즘의 우수성을 입증하였다.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2441-2443
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• 2003

This paper proposes an indirect adaptive fuzzy controller for general SISO nonlinear systems. No a priori information on bounding constants of uncertainties including reconstruction errors and optimal fuzzy parameters is needed. The control law and the update laws for fuzzy rule structure and estimates of fuzzy parameters and bounding constants are determined so that the Lyapunov stability of the whole closed loop system is guaranteed. The computer simulation results for an inverted pendulum system show the performance of the proposed robust adaptive fuzzy controller.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2702-2704
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• 2001

In this Letter, we propose a comprehensive design methodology of hybri'd Fuzzy controllers (HFC). The HFC comes as a form of a convex combination of a standard PID controller and a fuzzy controller. The design procedure dwells on the use of evolutionary computing (genetic algorithm) and an auto-tuning algorithm. The tuning of the scaling factors of the HFC is an essential component of the entire optimization process. A numerical study is presented and a detailed comparative analysis is also included.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1289-1292
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• 1993

Though fuzzy control is very popular at present, the application field of fuzzy system will be wider if we design it as a man-machine system. We suggest, in this paper, a man-machine cooperating system which makes easy the manual control of a triple inverted pendulum by simple fuzzy controller, and verify its effectiveness by experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.127-134
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• 2016

This paper presents a robust control of a reaction wheel inverted pendulum. To this end, a mathematical model is derived using physical laws, and then parameters in the model are identified as well. Based on the model, a robust position control is designed, which consists of two parts: swing-up control using passivity and robust stabilization control using LMI (Linear Matrix Inequality). When the pendulum starts to move, the swing-up control is applied. If the position of the pendulum is near the desired upright position, the control is switched to the robust stabilization control. This robust control is employed in order to deal with the uncertainties in the inertia of the pendulum dynamics. The performance of the proposed control scheme is validated not only simulation but also real experiment.

• 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 Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1871-1880
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• 2011

In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.570-576
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• 2012

In this research a moving platform for a mobile robot which can run with upright posture is proposed. It is able to stand with standing arms and run uprightly based on an inverted pendulum mechanism. Conventional mobile robots generally may equip 4 wheels or 3 wheels including a caster and have good statistic stability. They need a steering mechanism to choose which way to go since they have a square or rectangular configuration with multiple wheels. When a mobile robot meets a sharply perpendicular and narrow crossroad, it may need a special steering scheme such as going forward and backward repeatedly or it sometimes cannot even pass through the crossroad because of its size. The proposed moving platform for a mobile robot changes to a upright posture which has a small planar area and is able to pass through the crossroad. We propose a moving platform for a mobile robot with a inverted pendulum mechanism and standing arms which can make the mobile robot upright.