• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.128.3-128
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• 2001

In this paper we proposed that the speed of induction motor is controlled by a PI controller, which could control unknown motor using Neural Network for auto-tuning of the PI parameter. The parameters of the PI controller were adjusted to reduce the speed error of the controlled motor. The input parameters of the Neural Network controller are the speed, q-axis current, and speed reference of the induction motor respectively. The usefulness of proposed controller will be confirmed by simulation which we compare with conventional PI controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.93.2-93
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• 2001

This paper presents the implementation of fuzzy PI gain scheduling controller (FPICGS) for controlling flexible joint robot arms with uncertainties from time-varying load. The term FPICGS is called based on a combination of fuzzy PI control scheme with a set of rule bases. Principle of design for a FPICGS is given along with the implementation of the designed computer aided control system. The experiment reveals an effectiveness of the proposed control scheme for flexible joint robot arms driven by a DC motorhooked with a spring which both parameters are completely unknown parameters ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.503-507
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• 1989

A new decentralized adaptive controller design is proposed. In large scale interconnected system with unknown parameters, nonlinearities and bounded disturbances, even though the interconnection is weak, the controller parameter drifts due to the interconnection, so the decentralized adaptive controller comes to be unstable. The proposed new decentralized adaptive controller guarantees exponential convergence of tracking and parameter errors to residual sets which depend on the bound for the local disturbances and interconnections as well as on some arbitrary design parameters.

• Journal of applied mathematics & informatics
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• 제13권1_2호
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• pp.457-470
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• 2003

The comparison of two or more Lorenz curves of Pareto distributions of first kind under arbitrary order restriction is studied. The problem is turned out to be a statistical inference problem concerning scale parameters under order restriction. We assume that the location parameters of Palate distributions are completely unknown. In this paper the maximum likelihood estimation and likelihood ratio tests for and against order restriction are proposed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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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.

• International Journal of Reliability and Applications
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• 제12권1호
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• pp.41-48
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• 2011

This paper considers the maintenance model suggested by Jung and Park (2010) to adopt the Bayesian approach and obtain an optimal replacement policy following the expiration of NFRRW. As the criteria to determine the optimal maintenance period, we use the expected cost during the life cycle of the system. When the failure times are assumed to follow a Weibull distribution with unknown parameters, we propose an optimal maintenance policy based on the Bayesian approach. Also, we describe the revision of uncertainty about parameters in the light of data observed. Some numerical examples are presented for illustrative purpose.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.313-316
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• 1990

This paper proposes the design of the decentralized adaptive controllers which are an arbitrary interconnection of sub-systems with unknown parameters, nonlinear ities and bounded disturbances. In order to exponentially converge the state and parameter errors, robust decentralized adaptive controllers are developed for stabilization and tracking the parameters. In the simulation studies of the decentralized adaptive control of a two-area interconnected power system, the effectiveness of the proposed adaptive schemes is demonstrated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.225-225
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• 2000

We propose the hybrid robust controller for TDC(Time Delay Control) and SMC(Sliding Mode Control) method. TDC and SMC deal with the time-varying system parameters, unknown dynamics and unexpected disturbance. This controller is applied to follow the desired reference model for the uncertain time-varying overhead crane. The control performance is evaluated through simulation. The theoretical results indicate That the proposed controller shows excellent performance to an overhead crane with the uncertain time-varying parameters and disturbance.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.829-836
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• 2000

We shall derive Bayes estimators for he smaller and larger of two Pareto scale parameters with a common known shape parameter when the order of the scales is unknown and sample sizes are equal under squared error loss function. Also, we shall obtain biases and man squared errors for proposed Bayes estimators, and compare numerically performances for the proposed Bayes estimators.

• International Journal of Reliability and Applications
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• 제8권2호
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• pp.199-210
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• 2007

This paper presents estimations of the generalized Rayleigh distribution model based on grouped and censored data. The maximum likelihood method is used to derive point and asymptotic confidence estimates of the unknown parameters. The results obtained in this paper generalize some of those available in the literature. Finally, we test whether the current model fits a set of real data better than other models.