• 조명전기설비학회논문지
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• 제25권2호
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• pp.143-149
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• 2011

In this paper, IIR structures are proposed to reduce the computation complexity of the secondary-pass estimation in active noise control(ANC) systems. However, there are stability problems of using IIR models to reduce the computation complexity in ANC systems. To overcome these problems, we propose a stabilizing procedure of recursive least mean squares (RLMS) algorithms for eatimating the parameters of IIR models of the secondary path transfer functions. The multichannel ANC systems are implemented by using the TMS320C6713 DSP board to test the performance of computation complexity and stability of the proposed methods. Comparing the IIR filters with the FIR filters, the IIR filters can reduce 50[%] of the computation and obtain similar noise reduction result.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
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• pp.488-490
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• 1999

This paper describes the design of self-tuning speed controller for DC motor drive system using RLS(Recursive Least Squares) algorithm and Pole-Placement method. The model parameters, related to inertia and damping coefficient of motor, are estimated on-line by using RLS estimation algorithm. And a control signal is calculated by using pole placement method. Simulation and experimental results show that the proposed controller possesses excellent adaptation capability than a conventional PI/IP controller under parameter change.

• 제어로봇시스템학회논문지
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• 제5권8호
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• pp.932-940
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• 1999

In this paper, a new neural networks and neural network based sliding mode controller are proposed. The new neural networks are an mor self-recurrent neural networks which use a recursive least squares method for the fast on-line leammg. The error self-recurrent neural networks converge considerably last than the back-prollagation algorithm and have advantage oi bemg less affected by the poor initial weights and learning rate. The controller for suspension system is designed according to sliding mode technique based on new proposed neural networks. In order to adapt shding mode control mnethod, each frame dstance hetween ground and vehcle body is estimated md controller is designed according to estimated neural model. The neural networks based sliding mode controller approves good peiformance throllgh computer sirnulations.

• Journal of Power Electronics
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• 제10권3호
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• pp.270-276
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• 2010

In this paper, a capacitance estimation scheme for DC-link capacitors for single-phase AC/DC PWM converters is proposed. Under the no-load condition, a controlled AC current (30[Hz]) is injected into the input side, which then causes AC voltage ripples at the DC output side. Or, a controlled AC voltage can be directly injected into the DC output side. By extracting the AC voltage/current and power components on the DC output side using digital filters, the capacitance value can be calculated, where the recursive least squares (RLS) algorithm is used. The proposed methods can be simply implemented with software only and additional hardware is not required. From the experiment results, a high accuracy estimation of capacitances less than 0.85% has been obtained.

• 한국정밀공학회지
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• 제9권3호
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• pp.132-139
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• 1992

본 연구에서 디지탈 적응제어 시스템 설계를 위한 마이크로 컴퓨터 지원설계기법과 프로그램(DACS)을 개발 하였다. 이 프로그램은 Intel 80286 ghrdms 80386 CPU에 사용되는 GWBASIC 언어로 작성 되었고, 각 요소의 동특성을 모듈화 시키고, 차분방정식으로 표시하는 시뮬레이션 기법을 제시 하였다. 이 프로그램을 사용하면 디지탈제어에서 중요한 샘플링 시간과 A/D, D/A 변환기의 최적 Bit수를 결정할 수 있다. 적응제어 방법은 온라인 RLS(Recursive Least Squares) 파라메터 추정방법을 사용하였고, 실험결과와 잘 일치 되었다. 예제로서 공기예열시스템에 적응제어방법을 적용시켜 설계하다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.176-181
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• 1992

In this paper, an adaptive generalized predictive control(GPC) algorithm which minimizes a N-stage cost function is proposed. The resulting controller is based on GPC algorithm and can be used in unknown plant parameters as the parameters of one step ahead predictor are estimated by recursive least squares method. The estimated parameters are extended to G,P, and F amtrix which contain the parameters of N step ahead predictors. And the minimization of cost function assuming no constraints on future controls results in the projected control increment vector. Hence this adaptive GPC algorithm can be used for either unknown system or varing system parameters, and it is also shown through simulations that the algorithm is robust to the variation of system parameters. This adaptive GPC scheme is shown to have the same stability properties as the deterministic GPC, and requires small amount of calculation compared to other adaptive algorithms which minimize N-stage cost function. Especially, in case that the maximum output horizon is 1, the proposed algorithm can be applicable to direct adaptive GPC.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.51-55
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• 1995

An adaptive unified predictive control (UPC) algorithm is applied to a batch polymerization reactor for poly(methyl methancrylate) (PMMA) and the effects of controller parameters are investigated. Computational studies are performed for a batch polymerization system model developed in this study. A transfer function in parametric form is estimated by recursive least squares (RLS) method, and the UPC algorithm is implemented to control the reactor temperature on the basis of this transfer function. The adaptive unified predictive controller shows a better performance than the PID controller for tracking set point changes, especially in the latter part of reaction course when gel effect becomes significant. Various performance can be acquired by selecting adequate values for parameters of the adaptive unified predictive controller; in other words, the optimal set of parameters exists for a given set of reaction conditions and control objective.

• 전자공학회논문지B
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• 제30B권5호
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• pp.52-61
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• 1993

This paper deals with adaptive control method of a robot manipulator with one-flexible link. ARMA model is used as a prediction and estimation model, and adaptive control scheme consists of parameter estimation part and adaptive controller. Parameter estimation part estimates ARMA model's coefficients by using recursive least-squares(RLS) algorithm and generates the predicted output. Variable forgetting factor (VFF) is introduced to achieve an efficient estimation, and adaptive controller consists of reference model, error dynamics model and minimum prediction error controller. An optimal input is obtained by minimizing input torque, it's successive input change and the error between the predicted output and the reference output.

• The Journal of the Acoustical Society of Korea
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• 제15권3E호
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• pp.78-85
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• 1996

The set of admissible time-variations in the input signal can be separated into two categories : slow parameter changes and large parameter changes which occur infrequently. A common approach used in the tracking of slowly time-varying parameters is the exponential recursive least-squares(RLS) algorithm. There have been a variety of research works on the error analysis of the exponential RLS algorithm for the slowly time-varying parameters. In this paper, the focus has been given to the error analysis of exponential RLS algorithms for the input data with abrupt property changes. The voiced speech signal is chosen as the principal application. In order to analyze the error performance of the exponential RLS algorithm, deterministic properties of the exponential RLS algorithms is first analyzed for the case of abrupt parameter changes, the impulsive input(or error variance) synchronous to the abrupt change of parameter vectors actually enhances the convergence of the exponential RLS algorithm. The analysis has also been verified through simulations on the synthetic speech signal.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2006년도 전력전자학술대회 논문집
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• pp.381-383
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• 2006

A novel online capacitance estimation method for a DC-link capacitor in a three-phase AC/DC/AC PWM converter is proposed. A controlled AC voltage with a lower frequency than the line frequency is Injected into the DC-link voltage, which then causes AC power ripples at the DC output side. By extracting the AC voltage and power components on the DC output side using digital filters, the capacitance can then be calculated using the recursive least squares method. The proposed method can be simply implemented with only software and no additional hardware. Experimental results confirm that the estimation error is less than 0.2%.