• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.5
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• pp.837-844
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• 2013

This study performs erection of a pendulum hanging at a free end of an arm by rotating the arm to the upright position. A mathematical model of a rotary inverted pendulum system (RIPS) is derived. A brain emotional learning based intelligent controller (BELBIC) is designed and used as a controller for swinging up and balancing the pendulum of the RIPS. In simulations performed in the study, a pendulum is initially inclined at $45^{\circ}$ with respect to the upright position. A simulation is also performed for evaluating the adaptiveness of the designed BELBIC in the case of system variation. In addition, a simulation is performed for evaluating the robustness of the designed BELBIC against a disturbance in the control input.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.606-609
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• 1995

To stabilize a satellite, a spin stabilization method is used for attitude control. The spin stabilization uses the centrifugal force of a pendulum damper which is tilted long boom, to stabilize the unstable satellite. In this paper, an inverted pendulum system is implemented which is similar to the spin stabilization method. Study on the velocity of the rotation axis and the inverted pendulum's angle stability is shown. We designed a controller using a 32bit TMS320C31 DSP for the CPU and also performances by PLD control and Sliding Mode Control is compared.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.83-85
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• 1997

In this paper, a self-tunning fuzzy inference technique for stabilization of the inverted pendulum system is proposed. The facility of this self-tunning fuzzy controller which has swing-up control mode and a stabilization one, moves a pendulum in an initial natural stable equilibrium point and a cart in arbitrary position, to an unstable equilibrium point and a center of rail. Specially, the virtual equilibrium point(${\phi}_{VEq}$) which describes functionally considers the interactive dynamics between a position of cart and a angle of inverted pendulum is introduced. And comparing with the convention optimal controller, the proposed self-tunning fuzzy inference structure made substantially the inverted pendulum system robust and stable.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.656-663
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• 2007

A new dynamic balancing algorithm has been proposed to minimize the number of sensors necessary for the horizontal balancing of the mobile inverted pendulum while maintaining the same level of the commercial performance. The inverted pendulum technique is getting attention and there have been many researches on the Segway since the US inventor Dean Kamen commercialized. One of the major problems of the Segway is that many sensors are required for the control of the Segway, which results in the high price. In this research, a single gyro and a tilt sensor are fused to obtain the absolute tilt information, which is applied for the control of the mobile inverted pendulum. A dynamic balancing technique has been developed and applied for a robust control system against disturbances. The intelligent handling and stable curving of the Segway as a next generation mobile tool are verified with a human loading.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.11
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• pp.916-921
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• 2002

We presents a new method of constructing an equivalent T-S fuzzy model by using the sum of products of linearly independent scalar functions from nonlinear dynamics. This method exactly expresses nonlinear systems and automatically determines the number of rules. We design a stabilizing controller f3r ul inverted pendulum system by using the concep of parallel distributed compensation (PDC) and linear matrix inequalities (LMIs) based on the proposed T-S fuzzy modeling method. We show effectiveness of a systematically designed fuzzy controller based on the proposed T-S fuzzy modeling method through the simulation and experiment of an inverted pendulum system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1267-1271
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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.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.157-162
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• 2000

The inverted pendulum is a typical example of unstable systems and has been used for verification of designed control systems. It is also very popular in control education in laboratories, serving as a good example to show the utility of the state space approach to the controller design. This paper shows two kinds of experiment using inverted pendulum: one is the stabilization of a single spherical inverted pendulum by a plane manipulator using visual feedback, and the other is the state transfer control of a double pendulum. In the former experiment, the feedback stabilization using a CCD camera has major importance as an example of controller implementation with non-contact measurement. The latter involves the standard stabilizing regulation method and nonlinear control techniques. The details of the experimental systems, the control algorithms and the experimental results will be given.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.335-343
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• 2007

This paper deals with the method to estimate the friction in a system. We study a nonlinear friction model to estimate the friction in an inverted pendulum and approximate the friction model using fuzzy basis functions expansion. To demonstrate the friction observer using FBFs, we derive a update rule based on the error term that is formed by the output from a real system and observer output with a friction estimate. And two compensation algorithms to improve the response of an inverted pendulum are proposed. The first method that a observer parameter is updated in on-line and the friction is compensated at the same time. The second method is to compensate the friction with observer parameter estimated priori. The two methods is compared through the experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.28-34
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• 2012

Human generally uses three methods to keep balance. One of them is using reactive momentum such as swing an upper body or arms. In this study, we proposed a balancing controller for the reactive momentum method using an inverted pendulum. We simplified a human or a humanoid robot as a two-link inverted pendulum having two edges. In addition, we proposed a distinctive condition for controller transition. If a human is pushed, he has to change a balancing controller from using an ankle torque to using a reactive momentum or changing foot placement. When the balancing controller is changed from using an ankle torque to using a reactive momentum, it is required a proper timing to keep a stability and make smooth movement. In the experiment, the proposed controller and distinctive condition were verified.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.5-8
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• 2002

In this paper, we applied a PC interface and an embedded system in order to design a non-linear system and implement the PID algorithm as our control one. We used the inverted pendulum, one of the most generally used non-linear system models, to control uncertain factors in the environment. This paper showed how to use this non-linear system model to control the factors completely as well as to understand the PID algorithm. Furthermore, this paper applied and understood the embedded system.