• Journal of Mechanical Science and Technology
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• 제16권1호
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• pp.13-23
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• 2002

This paper presents inverse kinematic and dynamic analyses of HexaSlide type six degree-of-freedom parallel manipulators. The HexaSlide type parallel manipulators (HSM) can be characterized as an architecture with constant link lengths that are attached to moving sliders on the ground and to a mobile platform. In the inverse kinematic analyses, the slider and link motion (position, velocity, and acceleration) is computed given the desired mobile platform motion. Based on the inverse kinematic analysis, in order to compute the required actuator forces given the desired platform motion, inverse dynamic equations of motion of a parallel manipulator is derived by the Newton-Euler approach. In this derivation, the joint friction as well as all link inertia are included. Relative importance of the link inertia and joint frictions on the computed torque is investigated by computer simulations. It is expected that the inverse kinematic and dynamic equations can be used in the computed torque control and model-based adaptive control strategies.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.636-639
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• 1997

In this paper, a dynamic control scheme is proposed which not only compensates for the lateral dynamics and longitudinal dynamics but also deal with the yaw motion dynamics. Using the dynamic control technique, adaptive and learning algorithm together, the proposed controller is not only robust to disturbance and parameter uncertainties but also can learn the inverse dynamics model in steady state. Based on the proposed dynamic control scheme, a dynamic vehicle simulator is contructed to design and test various control techniques for 4-wheel steering vehicles.

• Journal of Mechanical Science and Technology
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• 제18권9호
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• pp.1519-1528
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• 2004

Atmospheric Re-Entry guidance is divided as longitudinal and lateral. This paper proposes a longitudinal reference trajectory and control law using the inverse dynamics method with pseudospectral Legendre method. Application of this method into Re-Entry problem forces a power of calculation time-reduction due to unnecessary of integration or any iteration as well as sufficient accuracy convergence. The used guidance scheme is time-to-go.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.987-992
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• 1988

In recent years there has been much interest in using light-weight, higher performance arms for both commercial and space-based applications, leading to the research of flexible robot manipulator. This paper is concerned with the trajectory control of a flexible arm using inverse dynamics. Inverse problems are important to robot control and programming, since they allow one to find the appropriate inputs necessary for producing the desired outputs. The input is obtained by the numerical inversion of Laplace transformation in the time domain. And we attempt the trajectory control experiment of a flexible arm using this calculated input. In this article we compare the numerical results with experimental results and can find good agreement. The results make clear that this technique has the good potential for the control of tip trajectory of flexible robot arms.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 춘계학술대회 논문집
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• pp.561-565
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• 2000

This paper deals with dynamic walking and inverse dynamic analysis of the IWR biped walking robot. The system has nine bodies of the multibody dynamics. and all of the .joints of them are made up of the revolute joints at first. The problem of redundant constraint in double support phase is solved by changing the type of the joints considering kinematic relation. To make sure of its dynamic walking, the movement of balancing weight is determined by which satisfies not only the condition of ZMP by applying the principle of D'Alembert but also the contact condition of the ground. The modeling of IWR and dynamic walking are realized using DADS.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.431-431
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• 2000

The modeling of 5-bar linkage robot manipulator dynamics by means of a mathematical and neural architecture is presented. Such a model is applicable to the design of a feedforward controller or adjustment of controller parameters. The inverse model consists of two parts: a mathematical part and a compensation part. In the mathematical part, the subsystems of a 5-bar linkage robot manipulator are constructed by applying Kawato's Feedback-Error-Learning method, and trained by given training data. In the compensation part, MLP backpropagation algorithm is used to compensate the unmodeled dynamics. The forward model is realized from the inverse model using the inverse of inertia matrix and the compensation torque is decoupled in the input torque of the forward model. This scheme can use tile mathematical knowledge of the robot manipulator and analogize the robot characteristics. It is shown that the model is reasonable to be used for design and initial gain tuning of a controller.

• 한국정밀공학회지
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• 제12권6호
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• pp.105-111
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• 1995

The inverse dynamic equations for 5 link robot including a closed chain have been derived. The closed chain is virtually cut open, and the kinematics and dynamics of the virtual open chain robot are analyzed. The constraints are applied to the virtually cut joints by the Jacobian matrix which represents the configuration of the closed chain. The topology of tree structrued open chain robot is described by a FATHER array. The FATHER array of a link indicates the link tha tis connected in the direction of base link. Based on the inverse dynamic equations, the torque sensitivity models of the 5 link robot have been developed. The sensitivity models characterize the sensitivity of the driving torque with respect to the link parameters. All the procedures are illustrated through the 2 link robot.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.608-610
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• 2004

In continuous annealing line (CAL), POSCO, the center position control (CPC) is an essential technique that renders the steel-strip to pass at the center of a roll in order to prevent the strip from skewing or breaking. The CPC algorithm currently installed on the steering roll in the heating section of CAL is to control the strip position by using the reverse phase of error from the center position, without considering the dynamics of strip horizontal movement. Such algorithm may, unfortunately, require a manual operation occasionally when the range of strip input becomes wide, causing the dynamics 0 be dominant. Other PID-type control is rarely used in automatic operation because the excess of response may occur when the discontinuous points such as welding joints pass through rolls. In this paper, we identify the CPC system by using off-line data and design a compensator for the excessive dynamics by using the adaptive inverse control. Simulation result depicts the improved reliability of the proposed CPC system.

• 소음진동
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• 제11권1호
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• pp.49-56
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• 2001

In this paper, two plant models, of which one is newly developed and the other one is the conventional one, of the focus servo system of DVD drive are presented and a two-degree-of freedom controller consisted of Inverse dynamics feedforward and LQG/LTR feedback controller is designed. The newly developed plant model is used to design the feedforward controller and the conventional model is used for the design of feedback controller. The output of newly developed model is the displacement of objective lens and the output of conventional model is the focus error of the DVD focus servo system. The displacement of the objective lens is estimated by the dynamics model of the DVD focus servo system. The disturbance rejection performance of the two-degree-of freedom controller is compared with that of an LQG/LTR one.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.14-19
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• 1993

In this paper, we proposed an indirect learning and direct adaptive control schemes using neural networks, i.e., composite adaptive neural control, for a class of continuous nonlinear systems. With the indirect learning method, the neural network learns the nonlinear basis of the system inverse dynamics by a modified backpropagation learning rule. The basis spans the local vector space of inverse dynamics with the direct adaptation method when the indirect learning result is within a prescribed error tolerance, as such this method is closely related to the adaptive control methods. Also hash addressing technique, similar to the CMAC functional architecture, is introduced for partitioning network hidden nodes according to the system states, so global neuro control properties can be organized by the local ones. For uniform stability, the sliding mode control is introduced when the neural network has not sufficiently learned the system dynamics. With proper assumptions on the controlled system, global stability and tracking error convergence proof can be given. The performance of the proposed control scheme is demonstrated with the simulation results of a nonlinear system.