• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.310-314
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• 2008

This paper proposes a very novel method which makes it possible that state feedback controller can be designed for unknown dynamic system with measurable states. This novel method uses the support vector machines (SVM) with its function approximation property. It works together with RLS (Recursive least-squares) algorithm. The RLS algorithm is used for the identification of input-output relationship. A virtual state space representation is derived from the relationship and the SVM makes the relationship between actual states and virtual states. A state feedback controller can be designed based on the virtual system and the SVM makes the controller with actual states. The results of this paper can give many opportunities that the state feedback control can be applied for unknown dynamic systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1000-1003
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• 1996

Nonlinear unified predictive control(UPC) algorithm was applied to the temperature control of a batch polymerization reactor for polymethylmethacrylate(PMMA). Before the polymerization reaction is initiated, the parameters of the process model are determined by the recursive least squares(RLS) method. During the reaction, nonlinearities due to generation of heat of reaction and variation of heat transfer coefficients are predicted through the nonlinear model developed. These nonlinearities are added to the process output from the linear process model. And then, the predicted process output is used to calculate the control output sequence. The performance of nonlinear control algorithm was verified by simulation and compared with that of the linear unified predictive control algorithm. In the experiment of a batch PMMA polymerization, nonlinear unified predictive control was implemented to regulate the temperature of the reactor, and the validity of the nonlinear model was verified through the experimental results. The performance of the nonlinear controller turned out to be superior to that of the linear controller for tracking abrupt changes in setpoint.

• 제어로봇시스템학회논문지
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• 제8권10호
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• 한국음향학회:학술대회논문집
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• 한국음향학회 2004년도 추계학술발표대회논문집 제23권 2호
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• pp.547-550
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• 2004

본 논문은 시스템 인식에서 RLS의 성능을 높이기 위한 한 방법으로 UDU 행렬 분해법을 바탕으로 한 recursive total least squares (RTLS) algorithm을 제안한다. 기존의 RTLS는 Power Method에 의거해서 recursive하게 만든 형태이어서 RLS와 거의 같은 구조이다. 그러나 본 논문에서는 일반적인 Power Method가 rank-1 update를 이용하기 때문에 ill-condition에 빠질 가능성이 높은 점을 감안하여, UDU 행렬 분해법을 사용한 RTLS방법을 제안하고, 그를 시스템 인식에 적용한다.

• 한국항공운항학회지
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• 제18권3호
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• pp.21-26
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• 2010

This paper deals with the precise parameter estimation of an air vehicle without a priori information. First, Recursive Least Squares technique, which is an equation error method and does not require any a priori information, is applied and then the extended Kalman filter is used to tune parameters more precisely. To show the performance, a nonlinear longitudinal missile model is simulated and the parameters are estimated. The results show that this consecutive application of the techniques gives a very good estimation performance.

• 한국정밀공학회지
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• 제12권11호
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• pp.110-117
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• 1995

This study presents and algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is applied for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm was tested on a check weigher. Discussions were extended to the development of noise reduction techniques and to the lagged introduction of objects on the moving plate. It turns out that the algorithm shows several desirable features suitable for real-time signal processing with a microcomputer, which are high precision and stability in noisy environment.

• 대한전기학회논문지:전력기술부문A
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• 제52권8호
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• pp.444-449
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• 2003

In this paper present Autonomous Adaptive Digital Over Current Relay for distribution networks which acts autonomous setting using the short circuit impedance measured by relay of power systems. Automation of relay setting is one of the basic requirements for distribution automation, although manual relay setting is used at present. The short circuit impedance from a power source in distribution networks essential for the Autonomous Relay Setting changes frequently in distribution networks. In this paper the short circuit impedance is calculated with voltage and current measured in real time operation of digital relay using the Recursive Least Squares. A new method of digital relay setting is introduced using the the short circuit impedance and load current.

• 한국정밀공학회지
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• 제11권6호
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• pp.136-142
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• 1994

This study presents an algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is described for te weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions are extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted real-time signal processing, which are high precision and stability in noisy environment.

• 한국정보통신학회논문지
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• 제11권12호
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• pp.2382-2390
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• 2007

본 논문에서는 비선형 앰프를 선형화 하는 다항식에 기반한 사전왜곡 알고리즘을 제안한다. 제안된 방식은 기존의 다항식 기반 방식과는 다르게 사후왜곡기의 도움 없이 직접 학습 방식으로 사전왜곡 계수를 추정한다. 먼저 앰프의 특성이 부분 선형으로 가정하여 알고리즘이 유도되고, 다음에 이 알고리즘을 앰프에 대한 어떠한 가정이 필요없는 구조로 변경한다. 제안된 사전왜곡기는 복소 계수를 가지는 다항식으로 구성되며 다항식의 계수는 RLS(recursive least squares)에 기반하여 찾게 된다. 컴퓨터 모의실험에 의하면 제안된 직접방식의 알고리즘이 기존의 간접 학습 방식에 비해 앰프의 초기 계수나 포화 영역에서 강인한 특성을 보인다.

• 한국음향학회지
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• 제29권1호
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• pp.18-23
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• 2010

RLS (Recursive Least Squares) 알고리즘은 적응 알고리즘의 대표적인 알고리즘이다. 하지만, 기본적인 RLS 알고리즘은 빠르게 움직이는 신호와 같은 비정상 (non-stationary) 신호환경에서는 좋은 성능을 가질 수 없다는 단점이 있다. 이를 해결하기 위하여 가변 망각 인자를 가지는 RLS 알고리즘이 등장하였으나, 기존의 가변 망각 인자 RLS 알고리즘은 연산량이 너무 많다는 단점이 있다. 본 논문에서는 이를 해결하기 위하여, 상대적으로 적은 연산량으로 AFF-RLS 알고리즘과 비슷한 성능을 내는 RLS 알고리즘을 제안한다.