• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.69-72
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• 1996

In this paper robust tracking control scheme using the new three-segment nonlinear sliding mode technique for nonlinear rigid robotic manipulator is developed. Sliding mode consists of three segments, the promotional acceleration segment, the constant velocity segment and the deceleration segment using terminal sliding mode. Strong robustness and fast error convergence can be obtained for rigid robotic manipulators with large uncertain dynamics by using the new three-segment nonlinear sliding mode technique together with a few useful structural properties of rigid robotic manipulator. The efficiency of the proposed method for the tracking has been demonstrated by simulations for two-link robot manipulator.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.575-591
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• 2006

In a previous research, we presented the Grid Method and confirmed it as a systematic and efficient problem formulation method for the task-oriented design of robot kinematics. However, our previous research was limited in two ways. First, it gave only a local optimum due to its use of a local optimization technique. Second, it used constant weights for a cost function chosen by the manual weights tuning algorithm, thereby showing low efficiency in finding an optimal solution. To overcome these two limitations, therefore, this paper presents a global optimization technique and an adaptive weights tuning algorithm to solve a formulated problem using the Grid Method. The efficiencies of the proposed algorithms have been confirmed through the kinematic design examples of various robot manipulators.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.4
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• pp.184-191
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• 2001

This paper proposes a prefilter type velocity compensating control system using modified chaotic neural networks for the trajectory control of robotic manipulator. Since the structure of modified chaotic neural networks(MCNN) and neurons have highly nonlinear dynamic characteristics, MCNN can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis robot manipulator is designed by MCNN. The MCNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on-line learning and the performance is excellent. The MCNN controller showed much better control performance and shorter calculation time compared to the RNN controller, Another advantage of the proposed controller could by attached to conventional robot controller without hardware changes.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1949-1954
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• 2005

One of control methods for underactuated manipulators is known as a switching control which selects a partially-stable controller using a prespecified switching rule. A switching computed torque control with a fuzzy energy region method was proposed. In this approach, some partly stable controllers are designed by the computed torque method, and a switching rule is based on fuzzy energy regions. Design parameters related to boundary curves of fuzzy energy regions are optimized offline by a genetic algorithm (GA). In this paper, we discuss on parameters obtained by GA. The effectiveness of the switching fuzzy energy method is demonstrated with some simulations.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.56-61
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• 2000

Majority of industrial robots are controlled by a simple independent joint control of joint actuators rather than complex controllers based on the nonlinear dynamic model of the robot manipulator. In this independent joint control scheme, the performance of actuator control is influenced significantly by the joint disturbance torques including gravity, Coriolis and centrifugal torques, which result in the trajectory tracking error in the joint control system. The control performance of a redundant manipulator under independent joint control can be improved by minimizing this joint disturbance torque in resolving the kinematic redundancy. A 3 DOF planar robot is studied as an example, and the dynamic programming method is used to find the globally optimal joint trajectory that minimize the joint disturbance torque over the entire motion. The resulting solution is compared with the solution obtained by the conventional joint torque minimization, and it is shown that joint disturbance can be reduced using the kinematic redundancy.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2341-2344
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• 2001

In recent years the neural network known as a sort of the intelligent control strategy is used as a powerful tool for designing control system since it has learning ability. But it is difficult for neural network controllers to guarantee the stability of control systems. In this paper we try connecting a radial basis function network to an adaptive control strategy. Radial basis function networks are simpler and easier to handle than multilayer perceptrons. We use the radial basis function network to generate control input signals that are similar to the control inputs of adaptive control using linear reparameterization of the robot manipulator. We adopt the saturation function as an auxiliary controller. This paper also proves mathematically the stability of the control system under the existence of disturbances and modeling errors.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.215-226
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• 2016

Modeling, control and implementation of a real redundant robot with five Degrees Freedom (DOF) of the SCARA (Selective Compliant Assembly Robot Arm) manipulator type is presented. Through geometric methods and structural and functional considerations, the inverse kinematics for redundant robot can be obtained. By means of a modification of the classical sliding mode control law through a hyperbolic function, we get a new algorithm which enables reducing the chattering effect of the real actuators, which together with the learning and adaptive controllers, is applied to the model and to the real robot. A simulation environment including the actuator dynamics is elaborated. A 5 DOF robot, a communication interface and a signal conditioning circuit are designed and implemented for feedback. Three control laws are executed in: a simulation structure (together with the dynamic model of the SCARA type redundant manipulator and the actuator dynamics) and a real redundant manipulator of the SCARA type carried out using MatLab/Simulink programming tools. The results, obtained through simulation and implementation, were represented by comparative curves and RMS indices of the joint errors, and they showed that the redundant manipulator, both in the simulation and the implementation, followed the test trajectory with less pronounced maximum errors using the adaptive controller than the other controllers, with more homogeneous motions of the manipulator.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.1-9
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• 2000

In this paper, we design a robust output feedback controller for robot manipulators with bounded parametric uncertainties using high-gain observer. The proposed control scheme with integral action improves tracking error due to limit of the robust feedback gains. High-gain observer is used to solve the noise problem with the joint velocity measurement. This controller avoids the limitation on the variation of unknown parameters and guarantees the uniformly ultimate boundedness of the closed-loop system. The performance of the proposed method is demonstrated by simulation on a 2-link manipulator.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.10
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• pp.53-59
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• 1990

In the control of robot manipulators, this paper presents a design of a new variable structure model following controller(VSMFC) using computed torque method (CTM). A sufficient condition for the existence of a sliding mode is derived by Lyapunov function. The reference model is a double integrators and the acceleration input consists of a proportional-derivative controller for the purpose of the stabilization of system and the desired performance. The proposed control scheme which consists of upper bounded and estimated value of each term of the manipulator of matrix inversion. Therefore the simulation results show that this controller is improved to the convergence of desired trajectories.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.869-877
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• 2004

This paper deals with motion planning algorithm for kinematically redundant manipulators that are not fixed to the ground. Differently from usual redundant manipulators fixed to the ground, the stability issue should be taken into account to prevent the robot from falling down. The typical ZMP equation, which is employed in human walking, will be employed to evaluate the stability. This work proposes a feed forward ZMP planning algorithm. The algorithm embeds the 'ZMP equations' indirectly into the kinematics of the kinematic model of a manipulator via a ZMP stability index The kinematic self motion of the redundant manipulator drives the system in such a way to keep or plan the ZHP at the desired position of the footprint. A sequential redundancy resolution algorithm exploiting the remaining kinematic redundancy is also proposed to enhance the performances of joint limit index and manipulability. In addition, the case exerted by external forces is taken into account. Through simulation for a 5 DOF redundant robot model, feasibility of the proposed algorithms is verified. Lastly, usual applications of the proposed kinematic model are discussed.