• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.155-160
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• 2006

In the paper a robust indirect adaptive fuzzy controller is proposed for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the proposed fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing and a supervisory fuzzy controller which emulates heuristic control strategy and arbitrate two control objectives. It is proved that the signals in the overall system are bounded. Simulation results are given to verify the proposed adaptive fuzzy control method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.164-167
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• 2004

In the paper is proposed a hierarchical adaptive fuzzy controller for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the hierarchical adaptive fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing, a forced disturbance generator which emulates heuristic control strategy, and a supervisory decision maker for the arbitration of two control objectives It is proved that all the signals in the overall system are bounded. Simulation results are given to verify the proposed adapt i ye fuzzy control method.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.67-74
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• 2013

This paper presents interaction force control between a balancing robot and a human operator. The balancing robot has two wheels to generate movements on the plane. Since the balancing robot is based on position control, the robot tries to maintain a desired angle to be zero when an external force is applied. This leads to the instability of the system. Thus a hybrid force control method is employed to react the external force from the operator to guide the balancing robot to the desired position by a human operator. Therefore, when an operator applies a force to the robot, desired balancing angles should be modified to maintain stable balance. To maintain stable balance under an external force, suitable desired balancing angles are determined along with force magnitudes applied by the operator through experimental studies. Experimental studies confirm the functionality of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.3
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• pp.233-239
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• 2013

This paper presents the analysis and control of the position of the COG (Center of Gravity) for a two-wheel balancing robot. The two-wheel balancing robot is required to maintain balance by driving two wheels only. Since the robot is not exactly symmetrical and its dynamics is changing with respect to moving parts, robust balancing control is difficult. Balancing performance becomes difficult when two arms hold a heavy object since the center of gravity is shifted out of the wheel axis. Novel design of a sliding waist mechanism allows the robot to react against the shift of the COG by moving the whole upper body to compensate for the imbalance of the mass as a counter balancer. To relocate the COG position accurately, the COG is analyzed by force data measured from two force sensors. Then the sliding COG mechanism is utilized to control the sliding waist position. Experimental studies are conducted to confirm the proposed design and method.

• 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.11 no.10
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• pp.888-894
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• 2005

In this paper, experimental studies of balancing a pendulum mounted on a wheeled drive mobile robot and its position control are presented. Main PID controllers are compensated by a neural network. Neural network learning algorithm is embedded on a DSP board and neural network controls the angle of the pendulum and the position of the mobile robot along with PID controllers. Uncertainties in system dynamics are compensated by a neural network in on-line fashion. Experimental results show that the performance of balancing of the pendulum and position tracking of the mobile robot is good.

• 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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• 2001.10a
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• pp.66.4-66
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• 2001

In this paper we have fabricated the two-dimensional Rod Balancing System which expands conventional one-dimensional inverted pendulum control system and designed its controller. The X-axis cart and Y-axis bar of the Rod Balancing System, which is composed of X-Y table, are actuated through timing belt by each of two geared DC motors, and the rod mounted on a X-axis cart can be brought to the desired position and maintained in a vertical position by motor-control. For the control of the Rod Balancing System, we used a fuzzy logic controller that is an approach to systems control when the exact mathematical model of the plant is unknown or the mathematical model is too complex to understand.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.190-196
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• 2014

In this paper, we get state equations based on wheel's rotation, tilt and steering are independent each other in balancing robot. Accordingly, we propose two LQR controllers which are appropriate for rotation and steering control of a balancing robot. And its superiority and appropriateness are demonstrated by a comparison to a PID method. Simulation results verify the possibility of upright balancing, rectilinear motion and position control. Moreover, experimental results show that it guarantees the performance to apply the two LQR controllers to balance the robot.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.23-29
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• 2016

This paper presents balancing control of a two-wheel mobile robot (TWMR). TWMR is aimed to maintain balance while moving. Although TWMR can be controlled by linear controllers such as PD controller, time-delayed controller is employed for robustness. Performances of PD controllers and time-delayed controllers are compared. Especially, experimental studies on different acceleration estimation for the time-delayed controller are conducted. Performances by different acceleration estimations of the balancing angle, of the position, and of both angle and position are compared empirically.