• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.138-141
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• 1989

In resent years, aided by the power and capability of digital computation, the techniques of Walsh Transform have been exploited for applications in commun- ication and signal processing. This paper presents an approach of FWT by using a 16- bit word-length micro- computer. This FWT implements an in-placed decimation-in-sequency algorithm which improves processing speed and memory storage. Several examples illustrate the process and demonstrate the power spectrum of FWT and that of FFT for the waveforms

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.850-852
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• 1999

This paper presents a new algorithm of three-level optimal control for non-linear large scale systems using fast walsh transform. Since the solution is obtained through the information exchange of coefficient vectors induced walsh transform of all levels, this algorithm is quick and convenient. The validity of the proposed method is checked in the simulation.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.302-304
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• 1992

This paper presents the method to reduce the order of high-order linear time invarient system via Walsh function. It is based on the matrix pseudoinverse algorithm to determine the parameters of the reduced model which minimize the sum of the squares of the errors between the reponses of the high-order system and a reduced model to a given input. This proposed method can be conveniently implemented with a computer. They will be very useful in the study of control system via Walsh function.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.95-96
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• 1986

시스템을 입력과 출력값 만으로 제어하고자 할 경우에는, 플랜트의 파라메타를 추정하면서 제어해 나가야 할 것이다. 이러한 경우에는, 귀환제어나 최적제어 형태로는 여러가지 문제점이 발견되어서, 최근에 적응제어가 많이 연구되고 있다. 이에는 Gain-Scheduling 방법, Self-tuning regulator 방법 및 model reference adaptive control 방법이 있다. Gain-Scheduling 방법은 미지의 파라메타가 plant에 있을지라도, 이를 즉시 예측할 수 있을 경우 보조변수 추정을 통하여 이득을 조절하여 시스템을 안정시키는 것이고, self tuning regulator는 보조변수를 직접 조정하여 시스템을 제어한다. 또 model reference adaptive control 방법은 기준모델을 정하여, 이에 따라 관측기 등을 통하여, 플랜트의 파라메타를 추정 제어해 나가는 것이다. 이때 기준 모델의 출력과 플랜트 출력사이의 오차를 어떻게 할 것인가? 추정되는 파라메타와 오차와의 대수관계 및 차수 등, 그 한계 해석이 최근의 MRAC 설계연구에 큰 과제가 되어 왔다. 이에 본 연구에서는 신호합성 및 해석에 뛰어난 기능이 있는 Walsh 함수를 이용하여, 간단한 Micro computer의 도움으로, 오차 함수를 합성하고, 미지의 파라메타를 추정하여, 시스템의 adaptive filter설계에의 가능성에 대하여 연구하고자 한다. 또 이를 실제 예를 들어 고찰하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.6
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• pp.529-534
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• 1988

This paper describes a new method to eliminate some selected harmonics in PWM waveforms using the Walsh series which substitute the linear algebraic equations for the nonlinear equations required in the Fourier series harmonic elimination. In addition, this method is simulated to synthesize periodic PWM waveforms and compare the Walsh analysis with the FOurier analysis, Experimental results are shown that a singel-phase PWM waveforms are identified with the proposed Walsh Series.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.415-422
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• 2000

This paper presents a new algorithm for hierarchical optimal control of nonlinear systems. The proposed method is simple because the solutions are obtained by only exchanging informations of coefficient vector based on interaction prediction principle and FWT(fast Walsh transform) in upper and lower level. Since we solve two point boundary problem with Picard's iterative method and the backward integral operational matrix of Walsh function to obtain the optimal vector of each independent subsystem, the algorithm is simple and its operation is fast without inverse matrix and kronecker product operation. In simulation, the proposed algorithm's usefulness is proved by comparison with the global optimal control methods.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.11
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• pp.514-521
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• 2001

This paper uses the distributed heating thin metal moving at constant velocity which are modeled as distributed parameter systems, and applies the Paley order of Walsh functions to high order partial differential equations and matrix partial differential equations. This thesis presents a new algorithm which usefully exercises the optimal control in the distributed parameter systems. In this paper, the excellent consequences are found without using the existing decentralized control or hierarchical control method.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.115-120
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• 2008

The EKF(Extended Kalman filter) method which is the state estimation algorithm of nonlinear stochastic system depends on the initial error and the estimated states. Therefore, the divergence of the estimated state can be caused if the initial values of the estimated states are not chosen as approximate real state values. In this paper, the demerit of the existing EKF method is improved using the EKF algorithm transformated by STWS(Single Term Walsh Series). This method linearizes each sampling interval of continous-time system through the derivation of an algebraic iterative equation without discretizing continuous system by the characteristic of STWS, the convergence of the estimated states can be improved. The validity of the proposed method is checked through comparison with the existing EKF method in simulation.

• Proceedings of the KIEE Conference
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• 2008.11b
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• pp.65-68
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• 2008

This paper presents the new adaptive optimal scheme for the nonlinear systems, which is based on the Picard's iterative approximation and Fast Walsh transform. It is well known that the Walsh function approach method is very difficult to apply for the analysis and optimal control of nonlinear systems. However, these problems can be easily solved by the improvement of the previous adaptive optimal scheme. The proposed method is easily applicable to the analysis and optimal control of nonlinear systems.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.2
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• pp.137-143
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• 1989

System modeling from input-output data is generally carried out in two steps. The first step is to determine the form of the model. In the second step, the parameters of the model in an appropriate form are estimated from input-output data. This paper presents a method, via single term Walsh functions, for simultaneous estimation of the order and the parameters of linear systems from input-output data. The estimation of the model order is based on minimizing an error function, which is defined by Desai and Fairman. Unknown system parameters are recursively estimated by the least square method.