• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.193-196
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• 2002

This paper proposes the control problem of an inverted pendulum system based on Sugeno-Type of fuzzy logic. The universal approximating capability, learning ability, adaptation capability and disturbance rejection are collected in one control strategy. The proposed scheme does not require an accurate dynamic model and the joint acceleration measurement, yet it guarantees asymptotic trajectory tracking. Experimental results perform with an inverted pendulum to show the effectiveness of the approach.

• The Journal of Korea Robotics Society
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• v.6 no.4
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• pp.317-322
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• 2011

An augmented state feedback controller for a Wheeled Inverted Pendulum (WIP) is proposed in this research. The augmented state feedback controller is able to keep the WIP returning to the origin. Generally, the WIP has both stable and unstable equilibrium points. To keep the WIP over the unstable equilibrium point, the WIP consistently is being controlled. A simple state feedback controller is letting the WIP out of the origin when the center of gravity of the WIP locates out of the schematic center line. In some case of applications, it may not be desirable that the WIP is drifting out of the initial location. The proposed augmented state feedback controller is able to keep the WIP at the initial location whether its center of gravity lies out of the center line or not. Numerical simulations are carried out to show the validation of the augmented sated feedback controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.267-273
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• 2007

This paper presents the implementation of an educational kit for intelligent system control education. Neural network control algorithms are presented and control hardware is embedded to control the inverted pendulum system. The RBF network and the MLP network are implemented and embedded on the DSP 2812 chip and other necessary functions are embedded on an FPGA chip. Experimental studies are conducted to compare performances of two neural control methods. The intelligent control educational kit(ICEK) is implemented with the inverted pendulum system whose movements of the cart is limited by space. Experimental results show that the neural controllers can manage to control both the angle and the position of the inverted pendulum systems within a limited distance. Performances of the RCT and the FEL control method are compared as well.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.496-501
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• 2012

An equilibrium point of a WIP (Wheeled Inverted Pendulum) with changing its center of gravity is derived and validated by various numerical simulations. Generally, the WIP has two equilibrium points which are unstable and stable one. The unstable one is interested in this study. To keep the WIP over the unstable equilibrium point, the WIP is consistently being adjusted. A state feedback controller for the WIP needs a control reference for the equilibrium point. The control reference can be obtained by studying an equilibrium point of the WIP based on statics. By using Lagrange method, this study is deriving dynamic equations of the WIP both with and without changing its center of gravity. Various numerical simulations are carried out to show the validation of the equilibrium point.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.228-236
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• 2012

In this paper, a controller for two wheeled inverted pendulum robot is designed to have more stable balancing capability than conventional controller. Fuzzy control structure is chosen for the two wheeled inverted pendulum robot, and fuzzy membership function factors for the controller are obtained for specified 3 users' weights using trial-and-error method. Next a neural network is employed to generate fuzzy membership function factors for more stable control performance when the user's weight is arbitrarily selected. Through the simulation study we find that the designed fuzzy controller using the neural network is superior to the conventional fuzzy controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.768-773
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• 2010

This paper presents the performance verification of the optimal state feedback controller via inverted pendulum systems. The proposed method generates the optimal control inputs satisfying both the constrained input and the performance specification. In addition, it reduces the steady-state error by adopting the integral control technique. In order to verify the performance of the proposed method, we apply both the proposed method and the general state feedback control to an inverted pendulum, CEM-IP-01 in the experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.536-544
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• 2011

In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1587-1596
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• 2016

This paper presents an interactive locomotion controller using motion capture data and inverted pendulum model. Most of the data-driven character controller using motion capture data have two kinds of limitation. First, it needs many example motion capture data to generate realistic motion. Second, it is difficult to make natural-looking motion when characters navigate dynamic terrain. In this paper, we present a technique that uses dimension reduction technique to motion capture data together with the Gaussian process dynamical model (GPDM), and interpolates the low-dimensional data to make final motion. With the low-dimensional data, we can make realistic walking motion with few example motion capture data. In addition, we apply the inverted pendulum model (IPM) to calculate the root trajectory considering the real-time user input upon the dynamic terrain. Our method can be used in game, virtual training, and many real-time applications.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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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.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1833-1838
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• 1991

This paper presents a stabilization technique for unstable systems. An inverted pendulum, which is a typical unstable mechanical system, is considered and stabilized by a nonlinear control. The stabilization problem in this system is related to that in postural control of human being. In this paper, the variable structure control (VSC) is applied to the stabilization problem. Robustness by the VSC and that by a conventional linear feedback controller are compared.