• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.289-292
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• 2001

This paper concerns with a receding horizon estimator (RHE) for discrete-time linear systems subject to constraints on the estimate. In solving the optimization for every horizons, the past all measurement data outside the horizon is discarded and thus the arrival cost is not considered. The RHE in the current work is a finite impulse response (FIR) structure which has some good inherent properties. The proposed RHE can be represented in the simple matrix form for the unconstrained case. Various numerical examples demonstrate how including constraints in the RHE can improve estimation performance. Especially, in the application to the unknown input estimation, it will be shown how the FIR structure in the RHE can improve the estimation speed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.4
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• pp.96-103
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• 2007

In this paper, we present a novel and numerically efficient algorithm for high resolution TOA(Time Of Arrival) estimation under indoor radio propagation channels. The proposed algorithm is not dependent on the structure of receivers, i.e, it can be used with either coherent or non-coherent receivers. The TOA estimation algorithm is based on a high resolution frequency estimation algorithm of Minimum-norm. The efficiency of the proposed algorithm relies on numerical analysis techniques in computing signal or noise subspaces. The algorithm is based on the two step procedures, one for transforming input data to frequency domain data and the other for estimating the unknown TOA using the proposed efficient algorithm. The efficiency in number of operations over other algorithms is presented. The performance of the proposed algorithm is investigated by means of computer simulations.. Throughout the analytic and computer simulation results, we show that the proposed algorithm exhibits superior performance in estimating TOA estimation with limited computational cost.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.350-355
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• 1997

The problem of mathematical model for an unknown system by measureing its input-output data pairs is generally referred to as state estimates. The state estimation problem is often of importance in its own right since we may want to know the value of the states. For instance, in navigation, we may take noisy positional fixes using satelite or radar navigation, and the estimator can use these measurements to provide accurate estimates of current position, hedaing, and velocity. And the state estimates can also be used for control purposes. Then it is very important to know the state of plant. In this paper, the theory of the minimization of a loss function was used to design the fuzzy system. Here, the used teory is Least Square Esimation method. This parametrization has the Linear in the parameters charcteristic that allows standard parameter estimation technique to be used to estimate the parameters of the fuzzy system. The combination of the fuzzy system and the estimation m thod then performs as a nonlinear estimator. If several fuzzy label are defined for the input variables at the antecedent part, the fuzzy system then behaves as a collection of nonlinear estimators where different regions of rules have different parameters. In simulation results, the fuzzy model controlled a difference in the structure between the actual plant and the fuzzy estimator. It is also proved that the fuzzy system is equivalent to its transformed system. therefore we was able to get the state space equation of system with the estimated paramater.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.337-340
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• 1997

In this paper we propose direct and indirect adaptive controllers for a nonlinear multivariable steam generating unit(200MW). In the direct adaptive scheme the estimation of the controller parameter are achieved from tracking error, while in the indirect approach the unknown parameter of the boiler system is estimated by the Hopfield network-based identifier. The performance of two proposed adaptive controllers is shown through simulations.

• 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.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.519-526
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• 1990

In this paper we propose the resolved motion controller using a neural network for a robot manipulator. Neural identifier designed by a neural network is trained by using a feedback force as an error signal. The identifier approximates the output of a unknown nonlinear system by monitoring both the input and the output of this system. If the neural network is sufficiently trained well, it does not require either strict modelling of the manipulator or precise parameter estimation. The effectiveness of the proposed controller is demonstrated by computer simulation using a two-link planar robot.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.6
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• pp.622-634
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• 2003

This paper is concerned with a computational method for recovering a crack shape of steam generator tubes of nuclear plants. Problems on the shape identification are discussed arising in the characterization of a structural defect in a conductor using data of eddy current inspection. A surface defect on the generator tube ran be detected as a probe impedance trajectory by scanning a pancake type coil. First, a mathematical model of the inspection process is derived from the Maxwell's equation. Second, the input and output relation is given by the approximate model by virtue of the hybrid use of the finite element and boundary element method. In that model, the crack shape is characterized by the unknown coefficients of the B-spline function which approximates the crack shape geometry. Finally, a parameter estimation technique is proposed for recovering the crack shape using data from the probe coil. The computational experiments were successfully tested with the laboratory data.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.9
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• pp.2312-2321
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• 1994

In this work the dynamics of an electromagnetic levitation system is described by a set of three first order nonlinear ordinary differential equations. The objective is to design a digital linear controller which takes the inherent instability of the uncontrolled system and the disturbing force into consideration. The controller is made by employing digital linear quadratic(LQ) design methodology and the unknown state variables are estimated by the kalman filter. The state estimation is performed using not only an air gap sensor but also both an air gap sensor and a piezoelectric accelerometer. The design scheme resulted in a digital linear controller having good stability and performance robustness in spite of various modelling errors. In case of using both a gap sensor and an accelerometer for the state estimation, the control input was rather stable than that in a system with gap sensor only and the controller dealt with the disturbing force more effectively.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.257-262
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• 1999

This paper proposes a composite fault detection and isolation method by combining the parameter estimation method[1] with the observer-based method[2] to take advantages of both methods. Some properties of the parameter estimation method and the observer-based method are revieved, and the composite algorithm is presented. To exemplify the performance of the method proposed, some simulations applied to remotely piloted vehicle are performed.