• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.341-349
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• 2004

In this paper, the decentralized neural network control of the reference compensation technique is proposed to control a 2-DOF inverted pendulum on an x-y plane. The cart with the 2-DOF inverted pendulum moves on the x-y plane and the 2-DOF inverted pendulum rotates freely on the x-y axis. Since the 2-DOF inverted pendulum is divided into two 1-DOF inverted pendulums, the decentralized neural network control is applied not only to balance the angle of pendulum, but also to control the position tracking of the cart. Especially, a circular trajectory tracking is tested for position tracking control of the cart while maintaining the angle of the pendulum. Experimental results show that position control of the inverted pendulum system is successful.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.124-124
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• 2000

In this paper, The PID controller for stabilization of an inverted pendulum system is proposed. The PR control rule is very common in control systems. It is the basic tool for solving most process control problem. We consider the inverted pendulum system containing two PID controllers. The first controls the angle of the pendulum. The second is used to control the position of the cart. We can show stabilization of the PID controller through simulation of the inverted pendulum system.

• 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.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.85-86
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• 2015

This paper is to study the inverted pendulum system of cart type by using the method of PID control. This system is that inverted pendulum maintain a constant balance from unstable state by moving a cart. It is controlled via the PID controller. PID controller is proposed to maintain a constant balance for nonlinear system such as the inverted pendulum system so PID control is widely used in the industrial field because of superior control performance, easy implementation and relatively simple structure. To design this system, it consist of Encorder and DC motor. Encorder is used to read the angle of the pendulum and DC motor is used to change the angle. We can verify results of experiment through the Matlab simulator via the inverted pendulum system of cart type.

• Journal of Ocean Engineering and Technology
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• v.23 no.2
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• pp.1-7
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• 2009

This paper presents a sliding mode controller based on Ackermann's formula and applies it to stabilizing a two-wheeled mobile inverted pendulum in equilibrium. The mobile inverted pendulum is a system with an inverted pendulum on a mobile cart. The dynamic modeling of the mobile inverted pendulum was established under the assumptions of a cart with no slip and a pendulum with only planar motion. The proposed sliding mode controller was based upon a class of nonlinear systems whose nonlinear part of the modeling can be linearly parameterized. The sliding surface was obtained in an explicit form using Ackermann's formula, and then a control law was designed from reachability conditions and made the sliding surface attractive to the equilibrium state of the mobile inverted pendulum. The proposed controller was implemented in a Microchip PIC16F877 micro-controller. The developed overall control system is described. The simulation and experimental results are presented to show the effectiveness of the modeling and controller.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.207-210
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• 1997

In this paper, a hierarchical fuzzy controller for stabilization of the inverted pendulum system is proposed. The facility of this hierarchical fuzzy controller which has a 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 hierarchical fuzzy inference made substantially the inverted pendulum system robust and stable.e.

• 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.

• 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 Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.304-309
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• 1998

In this paper, a fuzzy controller for stabilization of the inverted pendulum system is propose. The facility of this fuzzy controller which has a swing-up control mode and a stabilization one, moves a pendulum in an initial natural stable equilibrium point and a cart in arbitary 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 hierarchical fuzzy inference structur made substantially the inverted pendulum system robust and stable.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.4
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• pp.71-80
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• 1996

This paper presents stabilization and position control of the Inverted-Pendulum system with cart by using Evolution Strategies that is one of the Evolutionary Computation and is effective in searching real number. The control input of the Inverted-Pendulum is the element of chromosome corresponding to the divided space of Inverted-Pendulum state variable x, x, 0, 0 . In general, the larger the length of the chromosome is, the longer the time of evolution to search optimal solution is. So in this paper, we propose a scheme that reduce the state space by half by taking the method, that is, converting only the sign of the control input without obtaining separately for the symmetrical sections of the Inverted-Pendulum to improve the speed of Evolution, and improved the efficiency of the entire system in addition to the improvement of the chromosome's evolution time by carrying out the chromosome's evolutional process by two steps one of which is that cart is positioned near the control point and the other cart is positioned far from that point. We propose another method that is Neural Network-Evolution StrategiedNN-ES) Controller. We verify the effectiveness of the proposed control scheme by computer simulations.