• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1379-1382
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• 1997

We introduce a fast implementation of the adaptive transversal filter which uses least-mean-square(LMS) algorithm. The fast Hadamard transform(FHT) is used for the implementation of the filter. By using the proposed filter we can get the significant time reduction in computatioin over the conventional time domain LMS filter at the cost of a little performance. By computer simulation, we show the comparison of the propsed Hadamard-domain filter and the time domain filter in the view of multiplication time, mean-square error and robustness for noise.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.79-82
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• 2002

In this paper, we propose an adaptive repetitive control algorithm for the system the task of which is repetitive. The feedforward controller in the repetitive control system is modified by using the system parameter identifier in order to improve the convergence characteristics. The proposed algorithm is applied to the tracking control of a linear BLDC motor to which a periodic reference input is applied. It is illustrated by simulation results that the proposed adaptive repetitive control method yields better control performance than existing repetitive control even when modeling errors exist.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.392-398
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• 2009

A novel approach is presented to improve the array performance of the alternate mainbeam nulling in a linearly constrained adaptive array processor in coherent environment. The convergence parameters in the linearly constrained LMS algorithm with a unit gain constraint and a null constraint in the direction of the desired signal are adaptively estimated to reduce the error power between the desired signal and the array output in the 2-dimensional convergence parameter space. It is shown that the case for estimating the convergence parameter for the unit gain constraint with that for null constraint fixed performs best. Also, it is observed that the proposed method performs significantly better than conventional methods as the number of coherent interferences increases.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.6
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• pp.143-157
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• 1994

This paper is concerned with the position control of electrohydraulic servo system under parameter variation. An adaptive sliding mode control which uses the direct parameter estimation scheme, is proposed to design a robust controller for fast and accurate control of the system. It is shown that the adaptive sliding mode control algorithm is robust and effective in attaining fast and accurate position control of system under time-dependent parameter variation. It is also shown experimentally that chattering phenomena in a sliding mode control can significantly be reduced by using boundary layer technique, and that new approach in sliding mode control introducing a term proportional to the distance between the current state and the sliding surface in the control law is effective to obtain fast response and to increase stability of the system. Computer simulation on the dynamic performance of the control system is also presented.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.131-136
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• 1997

This paper represent the variable structure adaptive mode control technique which is new approach to implement the robust control of industrial robot manipulator with external disturbances and parameter uncertainties. Sliding mode control is a well-known technique for robust control of uncertain nonlinear systems. The robustness of sliding model controllers can be shown in contiuous time, but digital implementation may not preserve robustness properties because the sampling process limits the existence of a true sliding mode. the sampling process often forces the trajectory to oscillate in the neighborhood of the sliding surface. Adaptive control technique is particularly well-suited to robot manipulators where dynamic model is highly complex and may contain unknown parameters. Adaptive control algorithm is designed by using the principle of the model reference adaptive control method based upon the hyperstability theory. The proposed control scheme has a simple sturcture is computationally fast and does not require knowledge of the complex dynamic model or the parameter values of the manipulator or the payload. 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 of industrial robot control system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.956-962
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• 2013

Recently, sensorless controls, which eliminate position and speed sensor in a permanent magnet synchronous motor drive, have been much studied. Most sensorless control algorithms are based on the back-EMF and speed estimations which are obtained from the voltage equations. Therefore, the sensorless control performance is largely affected by the parameter errors of a motor. This paper investigates a novel adaptive control with the parameter error compensation for the speed sensorless control of a permanent magnet synchronous motor. The proposed parameter estimation is obtained from the d-axis current error between the real and estimated currents. The proposed algorithm is verified through the simulation and experimentation.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.375-378
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• 1991

This paper presents a design method of synchronous generator excitation controller using self-tuning PID algorithm. Controller parameter is determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameter of controller. minimum variance algorithm using the recursive leastsquare(RLS) indentification method is adopted and the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping and conversion characteristics. The results tested on a single machine infinite bus system verify that the proposed controller has better dynamic performances than conventional controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.11
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• pp.913-921
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• 1989

This paper deals with a pole placement indirect adaptive control algorithm for discrete-time linear plants with arbitrary zeros. The resulting closed-loop control system is shown to be globally stable subject to the assumptions that an external input is persistently exciting and a lower bound on the magnitude of the Sylvester resultant of the plant numerator and denominator polynomials is known. The problem of controllability of the plant estimate in indirect adaptive control is handled by using an extended parameter correction. The validity of the proposed control algorithm is assured through simulation for a second-order plant.

• Smart Structures and Systems
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• v.15 no.3
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• pp.735-749
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• 2015

The major difficulty of using Bayesian probabilistic inference for system identification is to obtain the posterior probability density of parameters conditioned by the measured response. The posterior density of structural parameters indicates how plausible each model is when considering the uncertainty of prediction errors. The Markov chain Monte Carlo (MCMC) method is a widespread medium for posterior inference but its convergence is often slow. The differential evolution adaptive Metropolis-Hasting (DREAM) algorithm boasts a population-based mechanism, which nms multiple different Markov chains simultaneously, and a global optimum exploration ability. This paper proposes an improved differential evolution adaptive Metropolis-Hasting algorithm (IDREAM) strategy to estimate the posterior density of structural parameters. The main benefit of IDREAM is its efficient MCMC simulation through its use of the adaptive Metropolis (AM) method with a mutation strategy for ensuring quick convergence and robust solutions. Its effectiveness was demonstrated in simulations on identifying the structural parameters with limited output data and noise polluted measurements.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.785-787
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• 1999

In this paper, recursive least square algorithm is presented to estimate the parameters of step motor under low-speed operation. Parameter estimation is important for compensating the input current by calculating the ratio of the motor torque constant and detent torque constant that causes torque-ripple in low-speed applications. On-line parameter estimation process is a preliminary procedure to apply step motor to adaptive control. Computer simulation shows that the estimated parameters converge in finite time.