• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.664-669
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• 2003

This paper proposes a swing-arm type dual-stage actuator, which consists of a PZT actuator for fine motion and a VCM(Voice Coil Motor) for coarse motion, for SFF ODD(Small Form Factor Optical Disk Drive), in order to achieve fast access speed and precise track following control. We focus our attention on the design and control of the PZT actuator, because there have been a lot of previous researches related to the VCM and dual-stage actuators. Due to the dual cantilever structure, the PZT actuator can generate precise translational tracking motion at its tip where optical pickup is attached at, and the effect of hysteric behavior of the PZT element is reduced. The dynamic model of the PZT actuator is derived by using the Hamilton's principle, and verified by comparing with the experimental frequency response. The sliding mode control is designed in order to be robust against modeling uncertainties. Simulations and experimental results confirm the effectiveness of the suggested control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.306-308
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• 1999

Recently 2DOF control system has been widely recognized to be efficient. The major merit of 2DOF control is the independency between tracking performance and feedback performance. But the design of two parameters of 2DOF control system is not much considered about the relation between the identification and the design. In the field of robust control, the joint control, which can combine the identification with the design, is investigated. Then are apply the joint control to the design of 2DOF control system, and verify the effectiveness by some simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.88-93
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• 1995

This paper presents a study using neural networks in the design of the tracking controller of robotic systems. Our strategy is to put to use the available knowledge about the robot manipulator, such as estimation models, in the contoller design via the computed torque method, and then to add the neural network to control the remaining uncertainty. The neural network used here learns to provide the inverse dynamics of the plant uncertainty, and acts as an inverse controller. In the simulation study, we verify that the proposed neural network controller is robust not only to structured uncertainties, but also to unstructured uncertainties such as friction models.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.884-889
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• 1990

In this paper, a new hybrid position control algorithm for the direct drive arm is proposed. The proposed control is composed of discrete feedforward component and continuous feedback component. The discrete component is the nominal torque which approximately compensates the strong nonlinear coupling torques between the links, while the continuous control is a modified version of sliding mode control which is known to have a robust property to the disturbances of system. For the proposed control law, we give sufficient condition which guarantees the bounded tracking error in spite of the modeling errors, and the efficiency of the proposed algorithm is demonstrated by the numerical simulation of a three link manipulator position control with payloads and parameter errors.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.649-655
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• 2007

In this paper, a time-delayed controller for position control of humanoid robot arms is designed and implemented on a field programmable gate array(FPGA) chip. The time-delayed control algorithm is simple to implement, and robust to reject disturbances. The time-delayed control method uses the one sample time-delayed previous information to cancel out uncertainties in the system. Since the sampling time is so fast with the current hardware technology, the time-delayed controller can be implemented. However, inertia values should be correctly estimated to have the better performance. The position tracking tasks of humanoid robot arms are tested to compare performances of several control algorithms including the time-delayed controller.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1286-1293
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• 2008

This paper proposes a realization of robust trajectory tracking for an industrial robot by using PD-sliding mode hybrid control. The PD control has a good performance in the transient period while the sliding mode control has robustness against the system uncertainties. The proposed control method is proposed for the control of a multi-joint robot by taking advantages of both the PD and sliding mode controls. The embodiment of distributed controllers that drive 4-DOF axes has evaluated through experiments with the multi-joint robot AT1. The PD-sliding mode algorithm which is proposed in this paper shows a good performance in the transient period and robustness against disturbances and This paper shows accuracy of end-effector.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.145-153
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• 2000

This paper discusses the dynamic modeling and robust control development for a differentially steered mobile robot subject to wheel slip according to high load. Consideration of wheel slip is crucial for high load applications such as construction automation tasks because wheel slip acts as a severe disturbance to the system. It is shown that the uncertainty terms due to the wheel slip satisfy the matching condition for the sliding mode control design. From the full dynamic model of the mobile robot, a reduced ideal model is extracted to facilitate the control design. The sliding mode control method ensures the dynamic tracking performance for such a mobile robot. Numerical simulation shows the promise of the developed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.7-12
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• 1990

In this paper, we propose a new manipulator control scheme based on the CMAG neural network. The proposed control consists of two components. The feedforward component is an output of trained CMAC neural network and the feedback component is a modified sliding mode control. The CMAC accepts the position, velocity and acceleration of manipulator as input and outputs two values for the controller : One is the nominal torque used for feedforward compensation(M1 network) and the other is the inertia matrix related information used for the feedback component(M2 network). Since the used control algorithm guarantees the robust trajectory tracking in spite of modeling errors, the CMAC mapping errors due to the memory limitation are little worth consideration.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.149-154
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• 1990

In this paper, simulation results of a robust digital tracking controller on a robotic manipulator are presented. The objective is to follow a ramp reference input with zero steady state error in the presence of a disturbance and system parameter variations. Some of the difficulties are caused by the Coulomb frictions, the disturbance due to the gravitational pull, the spring effect of a link between the drive motor and the manipulator arm. Another difficulty is that, because of the non-differentiable Coulomb friction, the digital control system cannot be represented as a discrete system. It is thus necessary to design the controller based on a discrete-continuous hybrid model. The controller is based on feeding back the state variables and augmenting the system by addition discrete integrators. The feedback gain parameters are obtained by applying the quadratic optimal control theory and then choosing the new weighting matrices to eliminate the limit cycle by using the describing function method for hybrid system.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.215-218
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• 2002

Gesture recognitions needed for various applications and is now gaining in importance as one method of enabling natural and intuitive human machine communication. In this paper, we propose a real time hand-signal recognition system in 3-dimensional space performs robust, real-time tracking under varying illumination. As compared with the existing method using classical pattern matching, this system is efficient with respect to speed and also presents more systematic way of defining hand-signals and developing a hand-signal recognition system. In order to verify the proposed method, we developed a virtual driving system operated by hand-signals.