• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.573-576
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• 1996

We propose robust control scheme for flexible joint manipulator in the presence of nonlinearity and mismatched uncertainty. The control is designed based on Lyapunov approach. The robust control which is based on the computed torque scheme and state transformation via implanted control is introduced. The design procedure starts with the construction of linearized subsystems via the computed torque method and then uses state transformation. With this approach we do not impose an upper-bound constraint on the inertia matrix in case it is known. Thus, this control can be applied to arbitrary manipulators. The resulting robust control guarantees practical stability for both the transformed system and the original system. The transformation is only based on the possible bound of uncertainty.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.10
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• pp.845-853
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• 2000

In this paper, we introduce a relationship between the sensitivity and the robustness of a system, and we propose a robust eigenstructure assignment scheme using a novel performance index which can consider the performance and the robustness of the system simultaneously. We also propose an assignment accuracy measure and a robustness measure which are used for the performance examination of the proposed robust eigenstructure assignment scheme. The usefulness of the proposed algorithm and the measures are verified by applying to controller design of a simple numerical example and the EMRAAT missile.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.10
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• pp.881-887
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• 2000

There are significant nonlinearities and uncertainties in hard disk drive actuators. In particular, pivot bearing nonlinearity and repeatable run-out make track-following control difficult as track density increases. In this paper, we design a robust track-following controller using a robust deterministic control scheme in which the pivot bearing nonlinearity and repeatable run-out are considered as uncertainties. Simulation study is conducted to evaluate the control performance of the proposed control scheme.

• Journal of KSNVE
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• v.10 no.4
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• pp.575-583
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• 2000

In this paper, we design a vibration control system that includes a 3-D.O.F. mass-spring-damper structure for the analytical model of a building that is excited at the base of this structure by an external dynamic force, and one Active Mass Damper(AMD) on the top of this structure to generate control forces fro attenuation of the structural response. Two robust controllers based on $\mu$-synthesis and H$\infty$ optimal control are designed for the structural system to show that the performance of a control system can be degraded by some parameter uncertainties such as mass, stiffness coefficients, and/or damping coefficients. The performance of the two controllers are compared in terms of nominal performance, robust stability and robust performance by simulations.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.736-741
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• 1992

The Stewart platform is one example of a motion simulator which generates 6 DOF motion in space by 6 actuators connected in parallel. The present SISO controllers are designed to track displacement command of each actuator computed from reference 6 DOF motion of platform by Stewart platform inverse kinematics. But this type of control can't cope with external load variation, geometric configuration of motion simulator, and different dynamic behavior of 6 DOF motion. In this paper, a multivariable controller using H- optimal control theory is designed for linerized simulator model with each actuator driving force as control input and platform 6 DOF motion as measured output. Nonlinear simulation result of the H$_{\infty}$ MIMO controller is not satisfied in steady-state characteristics. But the proposed H$_{\infty}$ + PI control scheme shows acceptable performance.e.e.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.667-675
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• 1999

In this paper, we propose a robust controller design of RTP(Rapid Thermal Processing) system using structured uncertainty approach. Using the weighted mixed sensitivity function, we solve the robust stability problem against disturbance and temperature variation, and design a $\mu$ controller using curve fitting method against structured uncertainty. Also the reduction method should be requried because of the difficulty of implementaion with the obtained high order controller. We dal with robust stability and performance of RTP system by the design of $\mu$ controller for original model and Schur balanced reduced model. Finally the simulation results are proposed to show the validity of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.3
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• pp.134-141
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• 1996

In this paper, we formulate the mathematical model for a single-stand rolling mill and design control systems for the thickness control at the exit of roll stand and for the tension control of the strip in the process. We propose a thickness controller based on the Internal Model Control structure which can be an effective application when the frequency components of the thickness deviation of the entry strip are known and, show how it can be appropriately combined with BISRA AGC method for a precise thickness control while maintaining the robustness against the modeling error of the mill modulus. It is illustrated by simulations that the proposed thickness control method gives better performance than existing methods and has the robustness against the modeling error of the mill modulus as well.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.1
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• pp.9-16
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• 1997

The method of designing robust two degree of freedom(2 DOF) controllers for linear systems with parameter uncertainties and unmodeled dynamics is presented in this paper. Robust performance condition that accounts for robust model matching of closed loop system and disturbance rejection is derived. Using the robust performance condition, the feedback controller is designed to meet robust stability and disturbance rejection specifications, while prefilter is used to improve the robust model matching properties. The $H^{\infty}$ and $\mu$ controller for six degree of freedom vehicle with parameter variations are designed and compared. Simulations for hydrodynamic parameter variations and disturbance are presented to demonstrate the achievement of good robust performance.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.10-14
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• 2004

We present a predictive control algorithm combined with the robust robot control that is constructed on the Lyapunov min-max approach. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about the model, it is an important trend to design a robust control law that guarantees the desired properties of the manipulator under uncertain elements. In the preceding robust control work, we need to tune several control parameters in the admissible set where the desired stability can be achieved. By introducing an optimal predictive control technique in robust control we can find out much more deterministic controller for both the stability and the performance of manipulators. A new class of robust control combined with an optimal predictive control is constructed. We apply it to a simple type of 2-link robot manipulator and show that a desired performance can be achieved through the computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.330-335
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• 1994

In this paper, adaprive control and sliding mode control are combined to implement the proposed adaptive sliding mode control(ASMC) algorithm which is new approach to the control of industrial robot manipulator with external disturbances and parameter uncertainties. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The contribution of this method is that the parameters of the sliding surface are replaced by time varying parameters whose are calculated by an adaptation algorithm, which forces the errors to follow the behavior of a reference error model. Simulation results show that the proposed method not only improves the performance of the system but also reduces the chattering problem of sliding mode control. Consequently, it is expected that the new adaptive sliding mode control algorithm will be suited for various practical applications.