• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.43-48
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• 2010

This article presents the experimental studies of controlling angle and position of the inverted pendulum system using neural network to compensate for errors caused due to fuzzy controller. Although fuzzy control method can deal with nonlinearities of the system, fixed fuzzy rules may not work and result in tracking errors in some cases. First, a nominal Takagi-Sugeno (TS) type fuzzy controller with fixed weights is used for controlling the inverted pendulum system. Then the neural network is added at the reference input to form the reference compensation technique (RCT)control structure. Neural network modifies the input trajectories to improve system performances by updating internal weights in on-line fashion. The back-propagation learning algorithm for neural network is derived and used to update weights. Control hardware of a DSP 6713 board to have real time control is implemented. Experimental results of controlling inverted pendulum system are conducted and performances are compared.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3057-3059
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• 1999

The inverted pendulum is an unstable, nonlinear system exposed to disturbances and its system parameters change. This paper presents the Time Delay Control design of the inverted pendulum using robot minipulator. The results obtained from a simulations indicated a reference tracking of the system. This paper will implement, the time delay control of the inverted pendulum using a robot manipulator, It will be that the time delay can control the inverted pendulum using a manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.507-507
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• 2000

In this paper, a kind of limit cycle of an inverted pendulum system is discussed. We propose a stabilization control law for such a limit cycle of an inverted pendulum system that the pendulum rotates periodically. Besides, the stabilization control law is extended so as to ensure not only stability of the limit cycle but also an L$_2$-gain disturbance attenuation in the presence of modeling error and viscosity friction.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.172-175
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• 1996

In the paper is proposed a hierarchical self-learning fuzzy controller for balancing and position control of an circular inverted pendulum system. To stabilize the pendulum at a specified position, the hierarchical fuzzy controller consists of a supervisory controller, a self-learning fuzzy controller, and a forced disturbance generator. Simulation example shows the effectiveness of the proposed method.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.1
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• pp.49-55
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• 2020

This paper presents the system modeling, analysis, and controller design and implementation with a inverted pendulum system in order to test Linear Quadratic control based robust algorithm for inverted pendulum robot. The balancing of an inverted pendulum robot by moving pendulum robot like as 'segway' along a horizontal track is a classic problem in the area of control. This paper will describe two methods to swing a pendulum attached to a cart from an initial downwards position to an upright position and maintain that state. The results of real experiment show that the proposed control system has superior performance for following a reference command at certain initial conditions.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.201-206
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• 2000

A priori information of object is needed to control in some well known control methods. But we can't always know a priori information of object in real world. In this paper, the inverted pendulum is simulated as a control task with the goal of learning to balance the pendulum with no a priori information using neural network controller. In contrast to other applications of neural networks to the inverted pendulum task, the performance feedback is unavailable on each training step, appearing only as a failure signal when the pendulum falls or reaches the bound of track. To solve this task, the delayed performance evaluation and the learning of nonlinear of nonlinear functions must be dealt. Reinforcement learning method is used for those issues.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.137-147
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• 2003

The fuzzy control and implementation of a new three-dimensional(3-D) inverted pendulum system are addressed. In comparison with conventional 1-D and 2-D systems, the 3-D inverted pendulum system is a proper benchmark system to simulate human's control action which includes the up and down motion to stabilize an inverted pendulum. To investigate the characteristics of the 3-D inverted pendulum system and to design of a fuzzy controller, we derive dynamic equations of the mechanism including a 3-axis cartesian robot and an inverted pendulum. We propose a design method of a fuzzy controller of the yaw and pitch angles of an inverted pendulum. In the design, the redundant degree-of-freedom(DOF) of the robot and the constrained workspace are taken into account. The performance of the proposed system is proved by experimental results using a developed PC-based Multi-Motion Control(MMC) board.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.188-191
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• 1996

In this paper, we derive dynamic equation of double pole inverted pendulum using Lagrangian equation, and design the fuzzy sliding mode controller. We demonstrate that the designed controller regulates double pole simultaneously regardless of cart position by computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.311-314
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• 1995

Biped locomotion can be simply modeled as a linear inverted pendulum mode. This model considers only the CG (center of gravity) of the entire system. But in real biped robot systems, the free-leg motion dynamics is not negligible. So if its dynamics is not considered in designing the reference CG motion, it is badly influence to the ZMP(zero moment point) position of the biped robot walking in the sagittal plane. Therefore, we modeled the biped locomotion similar to the linear inverted pendulum mode but considered the predetermined free-leg dynamics. To verify that the proposed biped locomotion is more stable than the linear inverted pendulum mode, we constructed a biped robot simulator and designed a serco controller to track both the reference motion of the free leg and the reference motion of CG of the biped robot using the computed torque control low. And through simulations, we verified that the proposed walking is better in stability than the one based on the linear inverted pendulum mode.

• Transactions of The Korea Fluid Power Systems Society
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• v.8 no.2
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• pp.1-7
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• 2011

An inverted pendulum mounted on a cart and actuated by a hydraulic servo cylinder was designed and built. Position information of the cart was acquired via a potentiometer and a angle of the pendulum was sensed by an incremental encoder. These were collected by a DAQ board and processed through the Real-Time Windows Target software(included in simulink). A simulink graphical program was implemented as a controller of the hydraulic system that governed the motion of the cart in order to maintain vertical balance of the inverted pendulum. The purpose of this study is to develop an electro-hydraulic inverted pendulum system for a modeling and controling the intrinsic unstable system. The simulation results were compared with the experimental and verified.