• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.224-230
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• 2015

In this paper, it is presented a learning controller for repetitive walking control of biped walking robot. We propose the iterative learning control algorithm which can learn periodic nonlinear load change ocuured due to the walking period through the intelligent control, not calculating the complex dynamics of walking robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of intelligent control to biped robotic motion is shown via dynamic simulation with 25-DOF biped walking robot.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.515-526
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• 2003

Tutorial contents of kinematics and dynamics of a wheeled drive mobile robot are presented. Based on the dynamic model, simulation studies of position tracking of a mobile robot are performed. The control structure of several position control algorithms using visual feedback are proposed and their performances are compared. In order to compensate for uncertainties from unknown dynamics and ignored dynamic effects such as slip conditions, neural network based position control schemes are proposed. Experiments are conducted and the results show the performance of the vision based neural network control scheme fumed out to be the best among several proposed schemes.

• The Journal of Korea Robotics Society
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• v.4 no.1
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• pp.17-24
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• 2009

This work deals with an intuitive method for a planar biped to walk, which is named Relative Trajectory Control (RTC) method. A key feature of the proposed RTC method is that feet of the robot are controlled to track a given trajectory, which is specially designed relative to the base body of the robot. The trajectory of feet is presumed from analysis of the walking motion of a human being. A simple method to maintain a stable posture while the robot is walking is also introduced in RTC method. In this work, the biped is modeled as a free-floating robot, of which dynamic model is obtained in the Cartesian space. Using the obtained dynamic model, the robot is controlled by a model-based feedback control scheme. The author shows a preliminary experimental result to verify that the biped robot with RTC method can walk on the even or uneven surfaces.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.89-94
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• 2001

The position control accuracy of a robot manipulator is significantly deteriorated when a long arm robot is operated at a high speed. This paper presents a very simple sliding mode control which eliminates multiple mode residual vibration in a robot manipulator. The neural network is used to avoid that sliding mode condition is deviated due to the change of system parameter and disturbance. This paper is suggested control system which designed by sliding mode controller using neural network. The effectiveness of proposed scheme is demonstrated through computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.754-758
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS320C50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator, In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters we determined by the pole-placement method. Performance of self-tuning adaptive controller is illusrated by the simulation and experiment for a SCARA robot.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.109-114
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• 2008

In this paper, a dynamic learning controller for robot manipulator is implemented using real-time operating system with capabilities of multitasking, intertask communication and synchronization, event-driven, priority-driven scheduling, real-time clock control, etc. The controller hardware system with VME bus and related devices is developed and applied to implement a dynamic learning control scheme for robot manipulator. Real-time performance of the proposed dynamic learning controller is tested and evaluated for tracking of the desired trajectory and compared with the conventional servo controller.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.235-240
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.14-19
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• 1997

In this paper, a new fuzzy sliding mode control algorithm is presented for trajectory control of robot manipulators. A fuzzy logic is applied to a sliding mode control algorithm to have the sliding mode gain adjusted continuously through fuzzy logic rules. With this scheme, te stability and the robustness of the proposed fuzzy logic control algorithm are proved and ensured by the sliding mode control law. The fuzzy logic controller requires only a few tuning parameters to adjust. Computer simulation results are given to show that the proposed algorithm can handle uncertain systems with large parameter uncertainties and external disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2051-2056
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• 2003

In this paper, a tele-manipulation in explosive ordnance disposal(EOD) applications is discussed. The ROBHAZ-DT2 is developed as a teleoperated mobile manipulator for EOD. In general, it has been thought that the robot must have appropriate functions and accuracy enough to handle the complicated and dangerous mission. However, the research on the ROBHAZ-DT2 revealed that the teleoperation causes more restrictions and difficulties in EOD mission. Thus to solve the problem, a novel user interface for the ROBHAZ-DT2 is developed, in which the operator can interact with various human senses (i.e. visual, auditory and haptic sense). It enables an operator to control the ROBHAZ-DT2 simply and intuitively. A tele-manipulation control scheme for the ROBHAZ-DT2 is also proposed including compliance control via force feedback. It makes the robot adapt itself to circumstances, while the robot faithfully follows a command of the operator. This paper deals with a detailed description on the user interface and the tele-manipulation control for the ROBHAZ-DT2. An EOD demonstration is conducted to verify the validity of the proposed interface and the control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.757-763
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• 2002

A newly designed haptic interface enables an operator to control a remote robot precisely. It transmits position information to the remote robot and feeds back the interaction force from it. A control algorithm of haptic interface has been studied to improve the robustness and stability to uncertain dynamic environments with a proposed contact dynamic model that incorporates human hand dynamics. A simplified hybrid parallel robot dynamic model fur a 6 DOF haptic device was proposed to from a real time control system, which does not include nonlinear components. LQC/LTR scheme was adopted in this paper for the compensation of un-modeled dynamics. The recovery of the farce from the remote robot at the haptic interface was demonstrated through the experiments.