• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.4
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• pp.309-314
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• 2009

This paper presents implementation of the adaptive neuro-fuzzy control method. Control performance of the adaptive neuro-fuzzy control method for a popular inverted pendulum system is evaluated. The inverted pendulum system is designed and built as an education kit for educational purpose for engineering students. The educational kit is specially used for intelligent control education. Control purpose is to satisfy balancing angle and desired trajectory tracking performance. The adaptive neuro-fuzzy controller has the Takagi-Sugeno(T-S) fuzzy structure. Back-propagation algorithm is used for updating weights in the fuzzy control. Control performances of the inverted pendulum system by PID control method and the adaptive neuro-fuzzy control method are compared. Control hardware of a DSP 2812 board is used to achieve the real-time control performance. Experimental studies are conducted to show successful control performances of the inverted pendulum system by the adaptive neuro-fuzzy control method.

• 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.

• 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.

• 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.

• 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.257-260
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• 1997

In this paper, the double inverted pendulum having a single actuator is built and the controller for the system is proposed. The lower link is hinged on the plate to free for rotation in the x-z plane. The upper link is connected to the lower link through a DC motor. The double inverted pendulum built can be kept upright posture by controlling the position of the upper link even though the proposed inverted pendulum has no actuator in lower hinge. The algorithm to control the inverted pendulum is consisted of a state feedback controller within a linearizable range and a fuzzy logic controller coupled with a feedback linearization control for the rest of the range. Concept of the virtual work is employed to drive the linearlized model for the state feedback controller. The feedback linearization controller drives a DC motor with the modified reference joint angle from the fuzzy controller which adjusts a upright posture of a proposed pendulum system. Finally, the experiments are conducted to show the validity of the proposed controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.875-885
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• 1999

This paper presents an application of LMI-based techniques to the mixed $H_2/ H_\infty$ control of an inverted pendulum. The linear model of the inverted pendulum represented by an LFR(Linear Fractional Representation) model of uncertainties is derived. Considered uncertainties are three nonlinear components and a parameter uncertainty Augmenting the LFR model by adding weighting functions, we get a generalized plant, for which we design a mixed $H_2/ H_\infty$ controller using the LMI technique. To evaluate control performances and robust stability of the mixed $H_2/ H_\infty$ controller designed, we compare it with the $ H_\infty$controller through the simulation and experiment. The mixed $H_2/ H_\infty$ controller shows the better control performances and robust stability than the $H_\infty$controller in the sense of pendulum angle.