• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.57-61
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• 1989

An adaptive control scheme is presented for uncertain systems whose uncertaintiy bounds are expressed as a linear combination of unknown functions of special form. Both the states and the parameter estimate errors of the closed-loop system are proven to be bounded. The regulation errors can be made sufficiently small by adjusting the design parameters. An application of the proposed method to the position control of a simple pendulum is given.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.589-591
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• 1999

In this paper, we consider the robust pole assignment for linear system with time-varying uncertainty. The considered uncertainty is an unstructured uncertainty. Based on Lyapunov stability and linear matrix inequality technique, we present a condition that guarantees the robust pole assignment inside a circular disk and the robust stability of uncertain linear systems. Finally, we show the usefulness of our results by an example.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.155.5-155
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• 2001

The robust predictive control law which use the bound estimation is proposed for uncertain robot manipulators. Since the control design of a real manipulator system may often be made on the basis of the imperfect knowledge about model, it´s an important tend to design a robust control law that will guarantee the desired performance of the manipulator under uncertain elements. In the preceeding work, the robust predictive control law was proposed. In this work, we propose a class of robust predictive control of manipulators with the bound estimate technique and fe stability based on Lyapunov function is presented.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.59.5-59
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• 2002

In this paper, we present a robust controller design method that can not only deal with the constant time delay plant but also an uncertain time delay one. For a constant time delay plant. The proposed DTC can independently adjust the set response and the disturbance response without any stability constraint. And in the uncertain time delay case, one can process the control design step with uncertainty norm bound. To verify real effectiveness, theoretical analysis and simulation results are given.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.687-693
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• 1989

A robust deterministic control for a class of singularly perturbed uncertain systems, where uncertainties are characterized deterministically rather than stochastically, is developed based mainly on information available on an uncertain reduced-order system. The deterministic control scheme is applied to the motion control of a n degree of freedom robotic manipulator. The parasitic actuator and sensor dynamics of the manipulator are explicitly considered in the stability analysis of the deterministic controller using a singular perturbation model. Simulation and experimental studies for a two degree of freedom, direct drive SCARA manipulator are conducted to evaluate the effectiveness of the derived control scheme.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.924-930
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• 1989

This paper presents the design of simple robust controller for a class of uncertain multivariable systems. We introduce switching dynamics instead of switching logics unlike variable structure control scheme. Also, we can construct the continuous control law from this switching dynamics and consequently remove the chattering motion. The dynamic equations of the range-space of a switching surface matrix C and uniform ultimate boundedness in the presence of parameter uncertainties are described mathematically.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.3
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• pp.22-30
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• 1993

In this paper, robust adaptive control algorithms which can be applied to unknown uncertain systems are suggested. Transform matrix for dividing states into "uncontrolled" states and "controlled" states and general searching procedure for the transform matrix which assign arbitrary n-1 eigen values for the uncontrolled subsystem of n-th orther single-input single-output systems of which state variables can be observable are also studied and utilized for the design of new-type controllers. We drived new-type control laws by using adaptive control theory and variable structure system and its stability is proved by using Lyapunov stability theory.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.742-746
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• 1992

This paper proposes a new linear robust state feedback controller for the linear discrete time systems which have uncertainties in the state and input matrices. The uncertainties need not satisfy the matching conditions, but only their bounds are needed to be known. The proposed controller is derived from the linear quadratic game problem, which solution is obtained via the modified algebraic Riccati equation. The controller guarantees the robust performance bound. The bound of the solution and the condition of the uncertainties, which can stabilize the uncertain system are explored.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.6
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• pp.1-10
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• 1997

This paper presents an adaptive optimal learning controller for uncertian robot systems which makes use fo simple DNN(dynamic neural network) units to estimate uncertain parameters and learn the unknown desired optimal input. With the aid of a lyapunov function, it is shown that all that error signals in the system are bounded and the robot trajectory converges to the desired one globally exponentially. The effectiveness of the proposed controller is hsown by applying the controller to a 2-DOF robot manipulator.

• Journal of Industrial Technology
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• v.15
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• pp.209-215
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• 1995

In this paper, a controller design method for uncertain linear systems by output feedback is proposed. This method utilizes the LQG/LTR procedure for systems with uncertainties described in the time domain. It is assumed that the uncertainties satisfy the matching conditions and their bounds are known. First, a robust state feedback controller design method is introduced. Then, it is asymtotically recovered for the output feedback system by the loop transfer recovery(LTR) method under a certain condition.