• 한국소음진동공학회:학술대회논문집
• /
• 한국소음진동공학회 2006년도 추계학술대회논문집
• /
• pp.474-478
• /
• 2006

It is becoming more significant to develop a rotary voice coil motor(VCM) type's actuator for small form factor (SFF) optical disk drive(ODD), as portables are getting more and more popularized nowadays. The actuator which is applicable to small-sized ODD with a compact flash(CF) II card size was developed and fabricated. The experimental results showed that the finite element(FE) model is different from the fabricated model. And so flexible mode frequencies did not satisfy specifications of small-sized ODD, and tuning. Tuning procedures were required to improve dynamic characteristics of the fabricated actuator through finite difference method(FDM). At first, design variables were extracted through parameter study and the tuned FE model was improved by design of experiment(DOE). Consequently, It was confirmed that the improved model was applicable to SFF ODD.

• 한국해양공학회지
• /
• 제29권6호
• /
• pp.488-498
• /
• 2015

This paper presents the dynamic model of an AUV called HW200 for underwater surveillance. The mathematical model of HW200 is briefly introduced, considering its shape. The maneuvering coefficients were initially estimated using empirical formulas and a database of vehicles with similar shapes. A motion simulator, based on Simulink of Mathworks, was developed to evaluate the mathematical model of the vehicle and to tune the maneuvering coefficients. The parameters were finely tuned by comparing the experimental results and simulated responses generated with the simulator by applying the same control inputs as the experiment. The velocity of HW200 in the tuning process was fixed at a constant forward speed of 1.83 m/s. Simulations with variable speed commands were conducted, and the results showed good consistency in the motion response, attitude, and velocity of the vehicle, which were similar to those of the experiment even under the speed variation. This paper also discusses the feasibility of its application to a model-based integrated navigation system (INS) using the auxiliary information on the velocities generated by the model.

• 한국컴퓨터정보학회논문지
• /
• 제24권11호
• /
• pp.51-59
• /
• 2019

웹에서 정보 접근에 대한 폭발적인 주문으로 웹 사용자의 다음 접근 페이지를 예측하는 필요성이 대두되었다. 웹 접근 예측을 위해 마코브(markov) 모델, 딥 신경망, 벡터 머신, 퍼지 추론 모델 등 많은 모델이 제안되었다. 신경망 모델에 기반한 딥러닝 기법에서 대규모 웹 사용 데이터에 대한 학습 시간이 엄청 길어진다. 이 문제를 해결하기 위하여 딥 신경망 모델에서는 학습을 여러 컴퓨터에 동시에, 즉 병렬로 학습시킨다. 본 논문에서는 먼저 스파크 클러스터에서 다층 Perceptron 모델을 학습 시킬 때 중요한 데이터 분할, shuffling, 압축, locality와 관련된 기본 파라미터들이 얼마만큼 영향을 미치는지 살펴보았다. 그 다음 웹 접근 예측을 위해 다층 Perceptron 모델을 학습 시킬 때 성능을 높이기 위하여 이들 스파크 파라미터들을 튜닝 하였다. 실험을 통하여 논문에서 제안한 스파크 파라미터 튜닝을 통한 웹 접근 예측 모델이 파라미터 튜닝을 하지 않았을 경우와 비교하여 웹 접근 예측에 대한 정확성과 성능 향상의 효과를 보였다.

• Transactions on Control, Automation and Systems Engineering
• /
• 제4권1호
• /
• pp.62-74
• /
• 2002

The tracking of a reference temperature trajectory in a polymerization batch reactor is a common problem and has critical importance because the quality control of a batch reactor is usually achieved by implementing the trajectory precisely. In this study, only energy balances around a reactor are considered as a design model for control synthesis, and material balances describing concentration variations of involved components are treated as unknown disturbances, of which the effects appear as time-varying parameters in the design model. For the synthesis of a tracking controller, a method combining the input-output linearization of a time-variant system with the parameter estimation is proposed. The parameter estimation method provides parameter estimates such that the estimated outputs asymptotically follow the measured outputs in a specified way. Since other unknown external disturbances or uncertainties can be lumped into existing parameters or considered as another separate parameters, the method is useful in practices exposed to diverse uncertainties and disturbances, and the designed controller becomes robust. And the design procedure and setting of tuning parameters are simple and clear due to the resulted linear design equations. The performances and the effectiveness of the proposed method are demonstrated via simulation studies.

• 한국생산제조학회지
• /
• 제5권2호
• /
• pp.63-72
• /
• 1996

In order to regulate the cutting force at a desired level during peripheral end milling processes a feedrate override Adaptive Control Constraint (ACC) system was developed. The feedrate override function was accomplished through a development of programmable machine controller (PMC) interface technique on the NC controller, Nonlinear model of the cutting process was linearized as an adaptive model with a time varying process parameter. An integral type estimator was introduced for on-line estimation of the cutting process parameter, Zero order hold digital control methodology which uses pole-assignment concept for tuning of PI controllers was applied for the ACC system. Performance of the ACC system wsa confirmed on the vertical machining center equipped with fanuc OMC through a large amount of experiment.

• ETRI Journal
• /
• 제18권3호
• /
• pp.161-170
• /
• 1996

We show that the electrically coupled Hindmarsh-Rose neuronal model exhibits various patterns of phase locking at fixed parameter value. Through the analysis of the effective coupling, the system is shown to be stabilized in one of these patterns according to the initial conditions. This corresponds to the parameter-tuning independent mode-switching mechanism that changes the electrical output of neuronal systems. It is also presented how the stable fixed points of the effective coupling which characterize the phase locking patterns depend on the external current.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
• /
• 제48권3호
• /
• pp.131-138
• /
• 1999

Generally, the digital controller has many advantages such as high precision, robustness to electrical noise, capability of flexible programming and fast response to the load variation. In this study, we have established proper mathematical equivalent model of Brushless DC (BLDC) motor and estimated the motor parameter by means of the back-emf measurement as being the step input to the controlled target BLDC motor. And the validity of proposed estimation method is confirmed by the test result of step response. As well, we have designed the reasonable digital controller as a consequence of the root locus method which is obtained from the open-loop transfer function of BLDC motor with hall sensor, and the determination of control gain for variable speed control. Here, revised Ziegler-Nichols tuning method is applied for the proper digital gain establishment, and the system stability is verified by the frequency domain analysis with Bode-plot and experimentation.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2021년도 추계학술발표대회
• /
• pp.446-448
• /
• 2021

In training a deep learning model, it is crucial to tune various hyperparameters and gain speed and accuracy. While hyperparameters that mathematically induce convergence impact training speed, system parameters that affect host-to-device transfer are also crucial. Therefore, it is important to properly tune and select parameters that influence the data loader as a system parameter in overall time acceleration. We propose an automated framework called Num Worker Tuner (NWT) to address this problem. This method finds the appropriate number of multi-processing subprocesses through the search space and accelerates the learning through the number of subprocesses. Furthermore, this method allows memory efficiency and speed-up by tuning the system-dependent parameter, the number of multi-process spawns.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2002년도 하계학술대회 논문집 B
• /
• pp.1165-1168
• /
• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

• Smart Structures and Systems
• /
• 제20권4호
• /
• pp.499-508
• /
• 2017

The ionic polymer-metal composite (IPMC) is an electroactive polymer material and has a promising potential as actuators for propulsion and locomotion in underwater systems. In this paper a physics based model is used to analyse the actuation dynamics of the IPMC propulsor. Moreover, proportional-integral (PI) controller is used for position control of the tip displacement of IPMC propulsor. PI parameter tuning is performed using particle swarm optimization (PSO) algorithm. Several performance indices have been used as an objective function to optimize the error of the system. Finally, the best tuning method is found out by comparing the results under various performance indices.