• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.10 no.5
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• pp.83-93
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• 1996

In this paper, a minimum variance control system is proposed and practically implemented, which is adequate to the induction motor speed control system with frequent load variation. Minimum variance control method is used as a control law and recursive least square method with selective forgetting factor is proposed and analyzed with general forgetting algorithm as an estimation method. Designed control system is based on PC-DSP structure for the purposed of easiness of applying adaptive algorithm. Through computer simulation and experimental results, it is verified that proposed control system is robust to the load variation and practical implementation is possible.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.455-458
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• 2002

A control of the body posture and movement is maintained by the vestibular system, vision, and proprioceptors. Especially, vestibular system has a very important function that controls the eye movement through vestibuloocular reflex and contraction of skeletal muscles through vestibulospinal reflex. However, postural disturbance caused by loss of vestibular function results in nausea, vomiting, vertigo and loss of craving for life. Lose of vestibular function leads to abnormal reflex of eye movements named nystagmus. Analysis of the nystagmus is needed to diagnose the vertigo, which is performed by means of electronystagmography (ENG). The purpose of this study is to develop a computerized system for data processing and an algorithm for the automatic evaluation of the slow component velocity (SCV) of nystagmus Induced by optokinetic(OKN) stimulation system. A new algorithm using recursive least square method (RLSM) to detect SCV of nystagmus is suggested in this paper. This method allows a fast and precise evaluation of the nystagmus, through artifact rejection techniques. The results are depicted in this paper.

• International Journal of Aeronautical and Space Sciences
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• v.6 no.2
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• pp.1-16
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• 2005

Adaptive control methods are studied for the Satellite to isolate vibration in spite of the nonlinear system dynamics and parameter uncertainties of disturbance. First, a centralized control scheme is developed based on the particle swarm optimization(PSO) algorithm and feedback theory to automatically tune controller gains. A simulation study of a 3 degree-of-freedom device was conducted to evaluate the performance of the proposed control scheme. Next, since a centralized control scheme is hard to construct model dynamics and not goad at performance when controller and systems environment are easily changed, a decentralized control scheme is presented to avoid these defects of the centralized control scheme from the point of view of production and maintenance. It is based on the adaptive control methodologies to find PID controller parameters. Experiment studies were conducted to apply the adaptive control scheme and evaluate the performance of the proposed control scheme with those of the conventional control schemes.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.87-95
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• 1998

This paper presents the method for the automatic tuning of a design weighting polynomial parameter of a generalized minimum-variance stochastic self tuning controller which adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design weighting polynomial parameters. The proposed self tuning method is simple and effective compared with other existing self tuning methods. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• Journal of Power Electronics
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• v.18 no.2
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• pp.558-572
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• 2018

In addition to its modular nature, a Hybrid Modular Multilevel Converter (HMMC) assembled from half-bridge and full-bridge sub-modules, is able to block DC faults with a minimum number of switching devices, which makes it attractive for high power applications. This paper introduces a control strategy based on the Root-Least Square (RLS) algorithm to estimate the capacitor voltages instead of using direct measurements. This action eliminates the need for voltage transducers in the HMMC sub-modules and the associated communication link with the central controller. In addition to capacitor voltage balancing and suppression of circulating currents, a fault tolerant control unit (FTCU) is integrated into the proposed strategy to modify the parameters of the HMMC controller. On advantage of the proposed FTCU is that it does not need extra components. Furthermore, a fault detection unit is adapted by utilizing a hybrid estimation scheme to detect sub-module faults. The behavior of the suggested technique is assessed using PSCAD offline simulations. In addition, it is validated using a real-time digital simulator connected to a real time controller under various normal and fault conditions. The proposed strategy shows robust performance in terms of accuracy and time response since it succeeds in stabilizing the HMMC under faults.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.37 no.2
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• pp.54-61
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• 2000

This paper presents the performance evaluation of channel estimation algorithm using RLS algorithm lot W-CDMA reverse link over Rayleigh fading channels. By obtaining BER(Bit Error Rate) performance through computer simulations, the RLS(Recursive Least Square) algorithm is compared with the existing WMSA(Weighted Averaging)(K=1,3) and constant gain algorithm. The channel structure, modulation and pilot patterns are applied to the ARIB (Association of Radio Industries and Business) and 3GPP (3rd Generation Partnership Project) ITU-R proposal for the IMT-2000. The BER performance of RLS algorithm with linear interpolation is similar to that of WMSA(K=1) and slightly superior to that of constant gain algorithm at low Doppler frequencies. Also, RLS algorithm performance is better than that of the WMSA(K=1,3) and constant gain algorithms about 4dB at BER=2.0$\times$$10^{-2}$ and Doppler frequencies $F_D$=320Hz. With increasing Doppler frequency, therefore, the BER performance of RLS algorithm with linear interpolation is superior to WMSA(K=L.3) and constant rain algorithms.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.11-22
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• 1999

Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.

• The Journal of the Acoustical Society of Korea
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• v.29 no.5
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• pp.303-313
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• 2010

This paper describes an acoustic communication receiver structure, which is designed for QPSK (Quadrature Phase Shift Keying) signal with 25 kHz carrier frequency and 5 kHz symbol rate, and takes samples from received signal at 100 kHz sampling rate. Based on the described receiver structure, optimum design parameters, such as number of taps of FF (Feed-Forward) and FB (Feed-Back) filters and forgetting factor of RLS (Recursive Least-Square) algorithm, of joint equalizer are determined to minimize the BER (Bit Error Rate) performance of the joint equalizer output symbols when the acquisition data in shallow water using implemented acoustic transducers is decimated at a rate of 2:1 and then enforced to the input of receiver. The transmission distances are 1.4 km, 2.9 km, and 4.7 km. Analysis results show that the optimum number of taps of FF and FB filters are different according to the distance between source and destination, but the optimum or near optimum value of forgetting factor is 0.997. Therefore, we can reach a conclusion that the proper receiver structure could change the number of taps of FF and FB filters with the fixed forgetting factor 0.997 according to the transmission distance. Another analysis result is that there are an acceptable performance degradation when the 16-tap-length simple filter is used as a low-pass filter of receiver instead of 161-tap-length matched filter.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11A
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• pp.1244-1252
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• 2004

In this paper, we derive some properties of linear detectors (zero forcing or minimum mean square error) at spatial multiplexing systems with alamouti's space-time block code. Based on the derived properies, this paper proposes low-complexity receivers. Implementing MMSE detector adaptively, the number of weight vectors to be calculated and updated is greatly reduced with the derived properties compared to the conventional methods. In the case of recursive least square algorithm, with the proposed approach computational complexity is reduced to less than the half. We also identify that sorted QR decomposition detector, which reduces the complexity of V-Blast detector, has the same properties for unitary matrix Q and upper triangular matrix R. A complexity reduction of about 50%, for sorted QR decomposition detector, can be achieved by using those properties without the loss of performance.