• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.548-553
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• 1992

In this paper and recursive version of orthogonal ARMA identification algorithm is proposed. The basic algorithm is based on Gram-Schmidt orthogonalization of automatically selected basis functions from specified function space, but does not require explicit creation of orthogonal functions. By using two dimensional autocorrelations and crosscorrelations of input and output with constant data length, identification algorithm is extended to cope slowly time-varying or order-varying delayed system.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.140-145
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• 1992

This paper presents a decentralized model reference adaptive control scheme for an interconnected linear system composed of a number of single-input single-output subsystems in which outgoing interactions pass through the measurement channel and are subjected to bounded external disturbances. The scheme can treat the unknown strength of interactions as well as uncertainties in subsystem dynamics, and allows for the case when the relative degree of each decoupled subsystem does not exceed two.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.367-369
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• 1986

Guaranteed cost control is a method applicable to a class of systems with uncertain parameters that guarantees an upper bound of the cost functional. This paper is concerned with a matrix decomposition technique used to yield a reasonable upper bound of the cost functional for a finite-time LQ regulator problem. The uncertain linear systems dealt with in this paper are described by a set of state equations of single-input phase-variable canonical form which contain unknown but bounded uncertain parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.554-559
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• 1986

This paper considers the problem of stabilizing a composite system formed by interconnecting a number of single-input single-output linear continuous systems. The problem is general in the sense that in addition to the standard assumption about the uncertainty of the subsystems, the strength of interconnections is assumed unknown. A method to design a local adaptive feedback control is first presented, and then the resultant closed-loop system is assured to be globally stable. Also, a numerical example is illustrated via computer simulation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.48-54
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• 1994

A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear systems with unkonwn time delay, order, and parameters. The algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extendedto recursive form by using two dimensional autocorrelations and crosscorrelations of input and output with constant data length. The proposed algorith can cope with slowly time-varying or order-varying delayed system. Various simulations reveal the performance of the algorithm.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.273-276
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• 1987

This paper presents a case-building algorithm which can control the design variables of which some variables are designated as the input (known) variables and the remainders are defined as the output (unknown) variables. The case-building algorithm can enhance the design ability by categorizing design case automatically. Common CAD programs for analysis and design of machine elements use a case-selection technique where a programmer set initially a few of design cases and users can only choose one of given cases. This paper also demonstrates the case-building algorithm by applying into CAD programs for power-screw design.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.4
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• pp.597-602
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• 1987

In this paper, an adaptive observe based upon the exponentially weighted least-squares method is implemented in the design of a model reference adaptive controller for an unknown time-invariant discrete single-input single-output linear plant. A method of selecting the state variable filter is proposed. In this scheme, all the past data are weithted exponentially with the weighting coefficient.

• 전기의세계
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• v.31 no.5
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• pp.361-367
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• 1982

The problem of parameter identification for multivariable stochastic linear systems from output measurements, which are corrupted by noises, is considered. A modified Luenberger's input/output canonical form is used for reducing the number of unknown coefficients. A computationally and conceptionally simple systematic procedure for parameter estimation is obtained using output correlation method. The estimates are shown to be asymptotically normal, unbiased and consistent. Numerical examples are presented to illustrate the identification method.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.693-695
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• 1997

This paper deals with the tracking control problem of robotic manipulators with unknown or changing dynamics. The torque input applied to the joint actuators is determined at every instance by the identification model that best approximates the robot dynamics. The best of the identified model is chosen by the proposed switching mechanism with fuzzy inference of the manipulator in an indirect adaptive controller architecture. Simulation results are also included to demonstrate the improvement in the tracking performance when the proposed method is used.