• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.328-328
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• 2000

In this paper, An inverted pendulum system is typical of a nonlinear model. We propose a stable the inverted pendulum with fuzzy controller and state observer of nonlinear system. we represent the fuzzy system as a Takagj-Sugeno fuzzy model in addition, full-order state observer of inverted pendulum. As the result show fuzzy controller of inverted pendulum with nonlinear model of full-order state observer.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.200-208
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• 2014

This paper presents the control of an inverted pendulum system using intelligent algorithms, such as fuzzy logic and neural networks, for advanced control education. The swing up balancing control of the inverted pendulum system was performed using fuzzy logic. Because the switching time from swing to standing motion is important for successful balancing, the fuzzy control method was employed to regulate the energy associated with the angular velocity required for the pendulum to be in an upright position. When the inverted pendulum arrived within a range of angles found experimentally, the control was switched from fuzzy to proportional-integral-derivative control to balance the inverted pendulum. When the pendulum was balancing, a joystick was used to command the desired position for the pendulum to follow. Experimental results demonstrated the performance of the two intelligent control methods.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.