• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.895-899
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• 2014

This paper presents the balancing control of a unicycle robot using air power. Since the robot has one wheel to move forward and backward, the balancing control is quite challenging. To control the balancing angle, the accurate angle estimation by a tilt and a gyro sensor is required a priori. A complementary filter is implemented to eliminate the defects of two sensors and to fuse together to estimate an accurate balancing angle. The optimal design of air ducts is found empirically. Experimental studies of the balancing control of a unicycle robot confirm that the robot is well regulated without falling down.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.786-791
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• 2017

In this paper, the run time of Li-polymer secondary cell with and without Active Balancing BMS is analyzed. The Active Balancing System using Flyback Converter with two-way power control facility, his designed for optimal characteristics of balancing. The run time of Li-polymer secondary cell is drastically increased employing the Flyback Convert Active Balancing BMS. The run time performance of Li-polymer secondary cell with or without Flyback Converter Active Balancing BMS is analyzed with the discharging and charging experiment of Li-polymer secondary cell.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.40-45
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• 2016

This paper presents the neuro-fuzzy control method for balancing a two-wheel mobile robot. A two-wheel mobile robot is built for the experimental studies. On-line learning algorithm based on the back-propagation(BP) method is derived for the Takagi-Sugeno(T-S) neuro-fuzzy controller. The modified error is proposed to learn the B-P algorithm for the balancing control of a two-wheel mobile robot. The T-S controller is implemented on a DSP chip. Experimental studies of the balancing control performance are conducted. Balancing control performances with disturbance are also conducted and results are evaluated.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.147-153
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• 2002

In the preceding research, the active balancing device, which is an electro-magnetic type, has been developed and active balancing method using influence coefficient method is also proposed. The stability of active balancing control is studied in this paper. A stable condition for active balancing control is derived by estimating errors of influence coefficients. A gain scheduling control using influence coefficients of the reference model is proposed when dynamic characteristic of rotor system is changed. The stability of the balancing method is verified by experiments.

• 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 the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.1-6
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• 2015

In this paper, a fuzzy control method is used for balancing a single-wheel robot. A single-wheel robot controlled by the PD control method becomes easily unstable since the flywheel tends to lean against one direction. In the previous research, we have used the gain scheduling method. To remedy this problem, in this paper, a fuzzy compensation technique is proposed to compensate for the balancing angle. The fuzzy control method compensates offset values at the balancing angle to prevent the gimbal from falling against one direction. Experimental studies of the balancing control performance of a single-wheel mobile robot validate the proposed control method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.736-740
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• 2014

This paper presents the driving and balancing control of an entertainment robot vehicle that can carry two persons. The entertainment robot vehicle is built with the purpose of carrying passengers with two wheels. It has two driving modes: a balancing mode with two wheels and a driving mode with three wheels. Three cases of different modes are verified by experimental studies. Firstly, a driving mode is tested with two passengers to check the functionality of the vehicle. Secondly, the balancing control performance is tested. Lastly, the balancing control performance under the disturbance is tested.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1185-1188
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• 1996

In this paper we present a genetic approach for trajectory control algorithm of balancing weight for IWR biped walking robot. The biped walking robot, IWR that was made by Automatic Control Lab. of Inha University has a trunk which stabilizes its walking by generating compensation moment. Trunk is composed of a revolute and a prismatic joint which roles balancing weight. The motion of balancing weight is determined by the gait of legs and represented by two linear second order ordinary differential equations. The solution of this equation must satisfy some constraints simultaneously to have a physical meaning. Genetic algorithm search for this feasible motion of balancing weight under some constraints. Simulation results show that feasible motion of balancing weight can be obtained by genetic algorithm.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.3
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• pp.188-196
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• 2016

For the balancing control of a one-wheel mobile robot, CMG (Control Moment Gyro) can be used as a gyroscopic actuator. Balancing control has to be done in the roll angle direction by an induced gyroscopic motion. Since the dedicated CMG cannot produce the rolling motion of the body directly, the yawing motion with the help of the frictional reaction can be used. The dynamic uncertainties including the chattering of the control input, disturbances, and vibration during the flipping control of the high rotating flywheel, however, cause ill effect on the balancing performance and even lead to the instability of the system. Fuzzy compensation is introduced as an auxiliary control method to prevent the robot from the failure due to leaning aside of the flywheel. Simulation studies are conducted to see the feasibility of the proposed control method. In addition, experimental studies are conducted for the verification of the proposed control.