• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.168-175
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• 1999

Unlike a general inverted pendulum system which is moved on the cart the proposed inverted pendulum system in this paper has an inverted pendulum which is moved on the two-degree-of-freedom parallelogram link. The dynamic equation of the pendulum system activated by the DD(Direct Drive)motor includes many nonlinear terms and has the high degree of freedoms. The problem is followed hat the exact mathmatical equations can not be analized by a general linear theory However the neural network trained by a simple learning method can control the dynamic system with hard nonlinearities. Learning procedure is the backpropagation algorithm with super-visory signal. The plant inputs obtained by the designed neural network in this paper can stabilize the pendu-lem and get the servo control. Experiment results have proce the effectiveness of the designed neural network controller.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.119-122
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• 2003

The aim of this paper is to propose a nonlinear controller for a single cart-type inverted pendulum using energy-based control scheme. Using a nonlinear model relating the angular position and velocity to the control input and a nonlinear controller is designed to regulate the angular position and velocity in the presence of input constraints. It is proved that the angular position and velocity converge to zero.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1775-1776
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• 2006

This paper deals with the problem of friction measurement of an inverted pendulum system using the regression analysis and proposes a solution. The approach taken in this study is getting the friction from a regression relational expression between the motor voltage and the cart velocity of an inverted pendulum system. The result to compensate LQR (linear Quadratic Regulator) controller with the friction which is measured in system, improved the performance of the system. Above all, the study has found that the proposed compensation of the friction reduces the oscillation of the cart position. In conclusion, the proposed method is useful when parameters in the given system model are not known.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.1
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• pp.116-121
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• 2018

In this paper, we propose the SIIM fuzzy Quasi-sliding mode controller for the system of a double inverted pendulum on a cart. Since it is difficult to handle this 6th-order system, we decoupled the entire system into three $2^{nd}$ order subsystem, and we designed the SIIM fuzzy Quasi-sliding mode controller for each subsystem, which was easy and did not require the derivation of the equivalent control. The stability of the entire system is guaranteed using Lyapunov function. The validity and robustness of the proposed controller are demonstrated through the computer simulation, and the results are compared with the results of former studies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.227-233
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• 1996

The Inverted Pendulum has been one of most popular nonlinear dynamic systems for the exploration of control techniques. This paper presents a new linear optimal control techniques and nonlinear neural network learning methods. The multiayered neural networks are used to add nonlinear effects on the linear optimal regulator(LQR). The new regulator can compensate nonlinear system uncertainties that are not considered in the LQR design, and can tolerated a wider range of uncertainties than the LQR alone. The new regulator has two neural networks for modeling and control. The neural network for modeling is used to obtain a more accurate model than the given mathematical equations. The neural network for control is used to overcome deficiencies by adding corrections to the linear coefficients of the LQR and by adding nonlinear effects on the LQR. Computer simulations are performed to show the applicability and a more robust regulator than the LQR alone.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.268-274
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• 2013

Any new method for controlling a nonlinear system has widely been reported. An inverted pendulum system has typically been used as a target system for demonstrating its usefulness. In this paper, we propose an algorithm to control a flexible joint cart based inverted pendulum system. Two carts are connected with a spring and one is a driving cart and the other is no driving cart with a pole. We here present a system modeling and a good fuzzy logic based control algorithm. We also introduce LQR (Linar Quadratic Regulator) technique for reducing the number of control variables. By using this technique, the number of input variables for a fuzzy logic controller is become only two not six. So the computational complexity is largely reduced. Moreover, a two-input fuzzy logic controller has a control rule table with a skew-symmetric property. And it will lead the design of a single-input fuzzy logic controller. In order to demonstrate the usefulness of the proposed method and prove the superiority of the proposed method, some computer simulations are presented.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.84-91
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• 2002

A new composite control method for a carriage balancing single inverted pendulum system is proposed and applied to swing up the pendulum and to stabilize it under the state constraint. The target inverted pendulum system has an extremely limited length of the cart(below 16cm). The proposed swing-up controller comprises a sliding mode control algorithm and an optimal control algorithm based on two regions: the region near the inverted unstable equilibrium position and the rest of the state space including the downward stable equilibrium position. The sliding mode controller uses a switching control action to converge along the specified path(hyperplane) derived from energy equation from a state around the path to desired state(standing position). An optimal control method is also used to guarantee the stability at unstable equilibrium position. Compared with the reported controllers, it is simpler and easier to implement. Experimental results are given to show the effectiveness of this controller.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.690-693
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• 2005

In this paper, a hybrid PD-servo state feedback control algorithm for swing up inverted pendulum system is proposed. It consists of two parts. The first part is the PD position control for swinging up the pendulum from the natural pendent position to around the upright position and the second part is the servo state feedback control for stabilizing the inverted pendulum in upright position. The first controller is PD controller and it is tuned to control the position of the pendulum by moving the cart back and forth until the pendulum swings up around the upright position. Then the second controller will be switched to stabilize the inverted pendulum in its upright position. The controller in this stage is the servo state feedback controller designed by pole placement. Experimental results of PD type swinging up control system, of stabilizing servo state feedback control system and of the proposed hybrid PD-servo state feedback control system to swing up and stabilize inverted pendulum show that the proposed method is effective and reliable for actual implementation while it is simple.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.92-99
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• 2004

In this paper, the decoupled neural network reference compensation technique (DRCT) is applied to the control of a two degrees-of-freedom inverted pendulum mounted on an x-y table. Neural networks are used as auxiliary controllers for both the x axis and y axis of the PD controlled inverted pendulum. The DRCT method known to compensate for uncertainties at the trajectory level is used to control both the angle of a pendulum and the position of a cart simultaneously. Implementation of an on-line neural network learning algorithm has been implemented on the DSP board of the dSpace DSP system. Experimental studies have shown successful balancing of a pendulum on an x-y plane and good position control under external disturbances as well.

• 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.