• 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.

• 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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• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.2
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• pp.243-253
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• 2002

This paper presents the system modeling, analysis, and controller design and implementation for a rotational inverted pendulum system(RIPS), which is an under-actuated system and has the problem of unattainable angular velocity state. A sliding mode controller using the parameterization of both the hyperplane and the compensator fur output feedback is applied to the RIPS. Also, to improve the performance of the control system, a disturbance observer which estimates the disturbance, parameter variation, and some modeling errors of RIPS with less computational effort is used together. The results of simulation and experiment show that the proposed control system has superior performance for disturbance rejection and regulation at certain initial conditions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.459-464
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• 1998

In this paper, we propose a stable fuzzy logic controller architecture for inverted pendulum,. In the design procedure, we represent the fuzzy system as a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller by considering each local state feedback controller and a supervisory controller, Unlike usual parallel distributed controller, one can design a global stable fuzzy controller without finding a common Lyapunov function by the proposed method. A simulation is performed to control the inverted pendulum to show the effectiveness and feasibility of the proposed fuzzy controller.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.918-926
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• 2001

In this paper, intelligent control method using neural network as a nonlinear controller is presented. Simulation studies for three link rotary robot are performed. Neural network controller is implemented on DSP board in PC to make real time computing possible. On-line training algorithms for neural network control are proposed. As a test-bed, a large x-y table was build and interface with PC has been implemented. Experiments such as inverted pendulum control and large x-y table position control are performed. The results for different PD controller gains with neural network show excellent position tracking for circular trajectory compared with those for PD controller only. Neural control scheme also works better for controlling inverted pendulum on x-y table.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2815-2817
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• 2005

This paper presents an experiment study on the control of a rotary-type inverted pendulum based on the Takagi-Sugeno (T-S) fuzzy model approach. A sufficient condition for stability of the T-S fuzzy control system is given via linear matrix inequalities (LMIs). State-feedback controllers for sub-systems are designed from the sufficient condition via change of variables which is one of the popular LMI techniques. Experimental results on a rotary-type inverted pendulum control show the feasibility of the T-S fuzzy model-based control method.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.859-861
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• 1999

This paper describes the development of a fuzzy gain scheduling scheme of PID controller for inverted pendulum system. Fuzzy rules and reasoning are utilized on-line to determine the controller parameters based on the error signal and its difference. Simulation results demonstrate that better control performance can be achieved in comparison with PID controller using pole placement to control of a Inverted pendulum.

• 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.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.179-181
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• 2007

This paper presents the desired position control of the mobile inverted pendulum system(MIP). The MIP is required to track the circular trajectory in the xy plane through the kinematic Jacobian relationship between the xy plane and the joint space. The reference compensation technique of the radial basis function(RBF) network is used as a neural network control method. The back-propagation teaming algorithm of the RBF network is derived and embedded on a DSP board. Experimental studies of tracking the circular trajectory are conducted.