• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.152-155
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• 1994

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.4_1
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• pp.397-409
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• 2021

This study proposes a new approach to implimentation of robust control and torque control response analysis based on monitoring simulator for smart factory. According to the physical properties of a flexible manipulator, a two time-scale approach, namely, singular perturbation ap proach, is further utilized for thorough analysis and general controller design. It is shown that asymptotic motional tracking can be effectively achieved, whereas the force regulation errors can be made arbitrarily small. For demonstration of the proposed technology performance, experiments of a eight joint flexible manipulator are performed for the proposed control method, and the reliability of proposed control results are illustrated based on monitoring simulator.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.10
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• pp.972-976
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• 2015

The objective of this research is to verify the quantitative efficiency of a bimanual robotic task. Bimanual robots can realize dexterous and complicated motions using two cooperating arms. However, its motion planning and control method are not simple for implementing flexible tasks such as assembly. In this paper, the proposed motion planning method is used to find an optimal solution satisfying a designed cost function and constraints with regard to the kinematics and redundancy of the bimanual robot. The simulation results show that the lifetime of the manipulator can be changed by the proposed cost function consisting of angular velocity and angular acceleration of each joint in the same assembly task.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.8-13
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• 1998

A tracking controller is presented for RLFJ(rigid link flexible joint) robot manipulators with only position measurements. The controller is developed based on the integrator backstepping design method and on the two observers: the first is simple linear form observer for the filtered link velocity errors and the other for the actuator velocities. The proposed controller achieves exponential tracking of link positions and velocities while keeping all internal signals bounded. It also guarantees exponential convergence of the estimated signals to their actual ones. Finally, simulation results are included to demonstrate the tracking performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.485-492
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• 2006

This paper deals with implementation of network for distributed control system of a humanoid robot ISHURO(Inha Semyung Humanoid Robot). A humanoid robot needs much degree of freedom structurally and much data for having flexible movement. To realize such a humanoid robot, distributed control method is preferred to the centralized one since it gives a compactness, modularity and flexibility for the controllers. For organizing distributed control system of a humanoid robot, a control processor on a board is needed to individually control the joint motor and communication technology between the processors is required to transmit its information within control time. The processor is DSP-based processor and includes CAN network on a chip. It shares the computational load such as monitoring the sensor information and controlling the actuator between each of modules. In this paper, the communication architecture is suggested and its message protocol are discussed including message structure, time consumption for transmission, and controller structure at the view of distributed control for a humanoid robot. All of the sequence are simulated with Matlab and then verified with real walking experiment by ISHURO.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1469-1473
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• 2004

We suggest how to program off-line robot path along shoes' outsole shape in the footwear buffing process by a 5-axis microscribe system like robot arms. This microscribe system developed consists a 5-axis robot link with a turn table, signal processing circuit, PC and an application software program. It makes a robot path on the shoe's upper through the movement of a microscribe with many joints. To do this, first it reads 5-encoder's pulse values while a robot arm points a shoes' outsole shape from the initial status. This system developed calculates the encoder pulse values for the robot arm's rotation and transmits the angle pulse values to the PC through a circuit. Then, Denavit-Hartenberg's(D-H) direct kinematics is used to make the global coordinate from robot joint one. The determinant is obtained with kinematics equation and D-H variable representation. To drive the kinematics equation, we have to set up the standard coordinates first. The many links and the more complicated structure cause the difficult kinematics problem to solve in the geometrical way. Thus, we can solve the robot's kinematics problems efficiently and systematically by Denavit-Hartenberg's representation. Finally, with the coordinate values calculated above, it can draw a buffing gauge-line on the upper. Also, it can program off-line robot path on the shoes' upper. We are subjected to obtaining shoes' outline points, which are 2 outlines coupled with the points and the normal vector based on the points. These data is supposed to be transformed into .dxf file to be used for data of automatic buffing robot. This system developed is simulated by using spline curves coupled with each point from dxf file in Autocad. As a result of applying this system to the buffing robot in the flexible footwear manufacturing system, it can be used effectively to program the path of a real buffing robot.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.411-418
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• 2005

This paper discusses an output-tracking control design method for Takagi-Sugeno fuzzy systems with parametric uncertainties. We first represent the concerned system as a set of uncertain linear systems. The tracking problem is then converted into a stabilization problem thereby leading to a more feasible control design procedure. A sufficient condition for robust practical output tracking is derived in terms of a set of linear matrix inequalities. A numerical example for a flexible-joint robot-arm model has been demonstrated, to convincingly show effectiveness of the proposed system modeling and control design.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1831_1832
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• 2009

본 논문에서는 유연관절 로봇 팔 제어를 위한 토크센서 기반의 외란에 강인한 제어기 설계를 다루고 있다. 로봇은 관절의 토크센서를 통해 관절에서 발생하는 토크의 측정이 가능하며 외란에 강인한 제어기 설계를 위해 외란 관측기가 적용 되었다. 외란관측기는 시스템에 작용하고 있는 외란을 상쇄하는 역할을 한다. 본 논문에서 설계된 제어기의 성능은 컴퓨터 모의실험을 통하여 확인하도록 한다.