• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.156-160
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• 1993

This paper presents a controller design to coordinate a robot manipulator under unknown system parameters and bounded disturbance inputs. To control the motion of the manipulator, an inverse dynamics control scheme is applied. Since parameters of the robot manipulators such as mass and inertia are not perfectly known, the difference between the actual and estimated parameters works as a disturbance force. To identify the unknown parameters, an inproved adaptive control algorithm is directly derived from a chosen Lyapunov's function candidate based on the Lyapunov's Second Method. A robust control algorithm is devised to counteract the bounded disturbance inputs such as contact forces and disturbing force coming from the difference between th actual and the estimated system parameters. Numerical examples are shown using three degree-of-freedom planar arm.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.714-719
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• 1994

This paper proposes a method of suboptimal control for DC servomotor using a neural network. First we consider a nonlinear observer which is constructed by using an approximated linear dynamics of the nonlinear system and a, neural network. The reccurent neural network is used for the learning of the dynamical system. Next we consider the nonlinear observer. Then, we apply the observer output to nonlinear optimal regulator and confirm the effectiveness by applying the method to the inverse pendulum system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.225-228
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• 1996

This paper concerns a SCARA type robot with the second arm flexible. Its equations of motion are derived by the Lagrangian mechanics. For controller design, the perturbation approach is taken to separate the original equations of motion into linear equations describing small perturbed motions and nonlinear equations describing purely rigid motion of the robot. To effect the desired payload motion, open loop control inputs are first determined based on the inverse dynamics of the latter. Next, in order to reduce the positional error during maneuver, an active vibration suppression is done. To this end, a feedback control is designed for robustness against disturbance on the basis of the linear equations and the LQR theory modified with a prescribed degree of stability. The numerical simulations results show the satisfactory control performance.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.698-701
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• 1996

A novel neural network control scheme is proposed to identify the inverse dynamic model of robot manipulator and to compensate for uncertainties in robot dynamics. The proposed controller is called reference compensation technique(RCT) by compensating at reference input trajectory. The proposed RCT scheme has many benefits due to the differences in compensating position and learning algorithm. Since the compensation is done outside the plant it can be applied to many control systems without modifying the inside controller. It performs well with low controller gain because the operating range of input values is small and the output of the neural network controller is amplified through the controller gain. The back-propagation algorithm is used to train and simulations of three link robot manipulator are carried out to prove the proposed controller's performances.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1871-1876
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• 2005

In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.397-400
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• 1992

Many dynamic control have been proposed; however, most of them are limited within stage of simulation study. The main reason is that the computations required for inverse dynamics are far beyond the ability of the present commercially available microprocessors. In this paper, In order to achieve real-time processing in robot dynamic control, a parallel processing computer for robot dynamic control is implemented using two transputer. Two transputer compute two degree of freedom robot. The transputer is a special purpose MPU for parallel processing. Transputers are used in networks to build a high performance concurrent system. A network of transputers and peripheral controllers is constructed using point-to-point communication. To gain most benifit from the transputer architecture, the whole system is programmed in OCCAM which is a high level language for concurrent applications. This control algorithm is applied to the RHINO SCARA type manipulator. We could taked about 438.6 microseconds to compute robot dynamic with two-processors.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1288-1293
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• 2003

This study predicts muscle forces acting on the lower extremity when the knee joint is in deep flexion. The whole bodies were approximated as a link model, and then the moment equilibrium equations at the lower extremity joints were derived for given reaction forces against the ground. Measurement of deep flexion was carried out by placing ten markers on the body. This study calculated the moment acting at each joint from the equations of force and moment, classified the complicated muscles around the knee joint. and then predicted the muscle forces to balance the joint moment. Two models were proposed in this study: the simpler one that consists of three groups of muscle and the more detailed one of nine groups of muscle.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1731-1734
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• 2003

We propose a unmaned integrating control system based-on Windows XP version Off-Line Programming System which can simulate a Robot model in 3D Graphics space in this paper. The robot with 4 and 6 axes modeled SM5 and AM1 respectively were adopted as an objective model. Forward kinematics, inverse kinematics and robot dynamics modeling were included in the developed off-line program. The interface between users and the off-line programming system in the Windows XP's graphic user interface environment was also studied. The developing language is Microsoft Visual C++. Graphic libraries, OpenGL, by silicon Graphics, Inc. were utilized for 3D Graphics.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.319-326
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• 2003

We propose a unmaned integrating control system based-on Windows XP version Off-Line Programming System which can simulate a Robot model in 3D Graphics space in this paper. The industrial robot with 4 and 6 axes modeled SM5 and AMI respectively were adopted as an objective model. Forward kinematics, inverse kinematics and robot dynamics modeling were included in the developed off-line program. The interface between users and the off-line programming system in the Windows XP's graphic user interface environment was also studied. The developing language is Microsoft Visual C++. Graphic libraries, OpenGL, by silicon Graphics, Inc. were utilized for 3D Graphics.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.510-518
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• 2004

The PID trajectory tracking controller for robotic systems shows performance limitation imposed by inverse dynamics according to desired trajectory. Since the equilibrium point can not be defined for the control system involving performance limitation, we define newly the quasi-equilibrium region as an alternative for equilibrium point. This analysis result of performance limitation can guide us the auto-tuning method for PID controller. Also, the quasi-equilibrium region is used as the target performance of auto-tuning PID trajectory tracking controller. The auto-tuning law is derived from the direct adaptive control scheme, based on the extended disturbance input-to-state stability and the characteristics of performance limitation. Finally, experimental results show that the target performance can be achieved by the proposed automatic tuning method.