• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.545-546
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• 2012

일반적으로 회전력이 발생하는 제어시스템에 있어서 발생되는 외란과 시스템의 동특성에 의해 발생되는 리플 등을 보정하기 위해 다양한 제어기법들이 연구되고 있다. 특히, 제어시스템에 존재하는 미지의 외란을 제거하기 위하여 AFC(Adaptive Feedforward Cancellation) 제어이론을 적용하여 미지의 외란에 대한 시스템의 안정성을 확보하려고 노력하고 있다. 그러나 기존의 AFC의 구현을 위하여 연속 시간제어시스템의 전달함수인 IMP(Internal Model Principle)를 이용하여 특정 주파수 영역에 대한 외란을 제거하고 있지만 보다 광범위한 영역에 대해서는 제어 성능은 아직 부족한 편이다. 본 논문에서는 기존의 PID 제어기를 이용한 위치제어에 있어서 발생할 수 있는 외란을 제거하기 위해 AFC 제어이론인 IMP 전달함수와 인공지능 기법인 Fuzzy 제어기를 추가로 설계하여 모터의 위치제어에 대한 성능과 외란 제어에 대한 성능을 제시하고자 한다.

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.409-413
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• 2005

The existing control techniques for the operation of a container crane satisfy the terminal condition of controlled variables, but the outcome of input computation is inadequate for the operation of the crane due to heavy movement of inputs. In this study, a new control technique employing a nonlinear model of the crane is proposed to compute the inputs approximated with the 4th-order Chevyshev function. The control objective of sum of absolute deviations is minimized, and the optimization is conducted with the simplex algorithm. The inputs and outputs computed from the proposed technique were compared with the results of the previous study to show that they give more stable crane operation than the existing control technique.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.3
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• pp.49-54
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• 2003

In this paper, we propose a controller with the self-organizing neural network compensator for compensating PID controller's response. PID controller has simple design method but needs a lot of trials and errors to determine coefficients. A neural network control method does not have optimal structure as the parameters are pre-specified by designers. In this paper, to solve this problem, we use a self-organizing neural network which has Back Propagation Network algorithm using a Gaussian Potential Function as an activation function of hidden layer nodes for compensating PID controller's output. Self-Organizing Neural Network's learning is proceeded by Gaussian Function's Mean, Variance and number which are automatically adjusted. As the results of simulation through the second order plant, we confirmed that the proposed controller get a good response compare with a PID controller. And we implemented the of controller performance hydraulic servo motor system using the DSP processor. Then we observed an experimental results.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.807-810
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• 2000

입체음향 시스템에서 모노음에 방향감을 제어하기 위한 방법으로 FIR 필터 형태의 머리전달함수( HRTF : Head-Related Transfer Function)를 사용한다. 그러나 이때 사용되는 FIR형태의 머리전달함수는 높은 차수를 가지고 있어 실시간 음상정위 처리가 어려운 문제점을 가지고 있다. 본 논문에서는 FIR 형태의 머리전달함수를 ARMA 시스템 인지기법을 이용하여 저차의 IIR필터 형태로 모델링하여 실시간 데이터 처리가 가능하도록 하였다. 본 논문에서 제안하는 ARMA 시스템 인지기법을 이용하게 되면 주어진 고차의 FIR형태의 머리전달함수를 다양한 안정성을 갖는 IIR모델들을 얻을 수 있으며, 이들 중 적절한 스펙트럼오차를 갖는 저차의 IIR모델을 선택 할 수 있다.

• Review of KIISC
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• v.32 no.1
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• pp.31-38
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• 2022

함수암호(functional encryption)는 프라이버시를 보호하면서 암호화된 데이터에 대한 연산을 수행할 수 있는 진화된 형태의 암호 기술이다. 비밀키를 가진 수신자에게 평문을 전부 제공하는 기존의 암호와 달리, 함수암호는 특정 연산에 대응하는 비밀키를 가진 수신자에게 평문에 대한 연산 결과만을 제공하기 때문에 데이터에 대한 유연한(fine-grained) 접근 제어가 가능하다. 인공지능과 같은 4차 산업혁명 시대의 대표 기술들은 데이터의 활용을 기반으로 하지만 이 과정에서 데이터 노출로 인한 사용자 프라이버시 침해 문제가 발생할 수 있다. 함수암호는 이러한 문제를 해결할 수 있는 기술로써, 프라이버시 보호와 데이터 경제 활성화를 위한 기반 기술로 활용될 수 있다. 본 논문에서는 함수암호 기술에 대한 개념을 설명하고 관련 연구 동향을 소개한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.165-177
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• 2000

A fuzzy controller need membership functions and the control rules depend on heuristic knowledge of expertises entirely. On account of, it is possible that a desired performance of a fuzzy controller can not be guaranteed or easily degraded under some circumstances such as a change of plant parameter which exporters do not considered. Therefore, in this paper we tried to increase the controller's efficiency by adjusting the control rules and the parameters of the membership functions by using a genetic algorithm. We also proposed the Self-Organizing Fuzzy Controller which uses the Fusion Method in order to minimize the number of control rules and to construct the intuitive controller. For validation of the proposed algorithm, we design the Autonomous Guided Vehicle Controller, then apply to variant condition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.973-976
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• 2009

Digital signal processing technique use to variety fields including communication. For these signal processing, FIR digital filter is representative. And for FIR digital filter designing, the window function is used to reduce the Gibbs phenomenon which occurs in the coefficient cutting process of the ideal filter. Therefore, in this paper to improve performance of digital filter, a high-order window function was applied. In this simulation, we compared a peak side-lobe and a transient characteristics with the existing window function.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.3
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• pp.273-281
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• 2001

In this paper, we propose a CMAC(Cerebellar Model Articulation Controller) neural network for controlling a non-linear system. CMAC is a neural network that models the human cerebellum. CMAC uses a table look-up method to resolve the complex non-linear system instead of numerical calculation method. It is very fast learn compared with other neural networks. It does not need a calculation time to generate control signals. The simulation results show that the proposed CMAC controllers for a simple non-linear function and a DC Motor speed control reduce tracking errors and improve the stability of its learning controllers. The validity of the proposed CMAC controller is also proved by the real-time tension control.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.173-183
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• 1998

In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.

• Journal of Advanced Navigation Technology
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• v.9 no.2
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• pp.87-92
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• 2005

An altitude control using a fuzzy controller was performed for a series of research for autonomous flight control of industrial unmanned helicopters. The 3m class gasoline engined unmanned helicopter was designed, and using the designed specifications, Takagi-Sugeno-Kang type fuzzy controller was designed. The input membership functions were generated using target altitude, altitude error and velocity of unmanned helicopter. With these membership functions, the control inputs for altitude control were calculated. These control input signal can control the main rotor's pitch and determine the velocity and altitude of the unmanned helicopter. Also, the altitude control performance of the designed fuzzy controller was evaluated by computer simulations