• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.604-610
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• 2007

Injection molding is the most common method of shaping plastic resins for manufacturing a variety of parts. This injection molding is accomplished by injection molding machines (IMM) which consists of a hewer, a reciprocating screw, barrel assembly, and an injection nozzle. The plastic resin is fed to the machine through the hopper and it should be heated to the target melting temperature, which depends on material properties, as closely as possible with very small temperature overshoot in the barrel. Since the barrel, which has temperature dependent specific heat and thermal conductivity in the operating temperature range, is heated by the several electric heater bands, it is not an easy task to control the temperature of the barrel owing to the interference of neighboring heaters and its material properties. Though PID controller with auto-tuning capability is widely adopted in the nm, the auto-tuning process should be carried out whenever the operating temperature is changed significantly. Recently, though the predictive controller is developed and shows good performance, it has drawbacks: 1. Since the heat transfer modeling process is very complicated and should be carried out again when the barrel is changed, it is somewhat inappropriate in the field. 2. The controller performance is not validated in whole operating temperature range. In this paper, cascade type simple PI controller with input restriction is proposed to find the possibility of controlling the barrel temperature in the whole operating temperature range. It is shown by experiment that the proposed controller shows good performance. This result can be applied to design of PI controller with auto-tuning capability.

• Journal of Auto-vehicle Safety Association
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• v.13 no.4
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• pp.39-52
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• 2021

This paper presents a longitudinal acceleration controller that can be applied to real vehicles (nonlinear and time-varing systems) with only a simple experiment regardless of the type of vehicle and the control interface structure. The controller consists of a feedforward term for fast response, a zero-throttle acceleration compensation term, and a feedback term (P gain) to compensate for errors in the feedforward term, and another feedback term (I gain) to respond to disturbances such as slope. In order to easily apply it to real vehicles, there are only two tuning parameters, feedforward terms of throttle and brake control. And the remaining parameters can be calculated immediately when the two parameters are decided. The tuning procedure is also unified so that it can be quickly and easily applied to various vehicles. The performance of the controller was evaluated using MATLAB/Simulink and Truksim's European Ben model. In addition, the controller was successfully implemented to 3 medium-sized vehicle (HMC Solati), which is composed of different control interface characteristic. Vehicle driving performance was evaluated on the test track and on the urban roads in Siheung and Seoul.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.2
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• pp.89-93
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• 1997

As industry gets rapidly automatic, D.C servo motor which is controlled by a PI controller needs accurate control. However, when a system has various characters, it is very difficult to guarantee its accuracy. In this paper, rule-based auto-tuning PI controller for motor speed control system is presented as a way of solving this problem. Some rules are based on Ziegler-Nichols step response and expert knowledge. Control parameters are determined by error, slope, steepest slope point, and permiSSIon overshoot. The accuracy of control is demonstrated by a computer s mulation .

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.5
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• pp.499-508
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• 2002

In this paper, a novel wireless parallel operation algorithm of N+l redundant UPS system with no control interconnections for load-sharing is presented. The proposed control system eliminates the sensing noise and interconnections interference of conventional parallel operation system. To reduce a reactive power deviation in wireless control method, this technique automatically compensates for inverter parameter variation and line impedance imbalances with wireless auto-tuning method. In addition, to increase reliability on transient characteristics of parallel operation, a virtual injected impedance is adopted to eliminate a circulation current among inverter modules. Simulation results are provided in this paper to prove the proposed novel wireless algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.464-470
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• 2004

We propose an enhanced backpropagation algorithm by auto-tuning of learning rate using fuzzy control system for performance improvement of backpropagation algorithm. We propose two methods, which improve local minima and loaming times problem. First, if absolute value of difference between target and actual output value is smaller than $\varepsilon$ or the same, we define it as correctness. And if bigger than $\varepsilon$, we define it as incorrectness. Second, instead of choosing a fixed learning rate, the proposed method is used to dynamically adjust learning rate using fuzzy control system. The inputs of fuzzy control system are number of correctness and incorrectness, and the output is the Loaming rate. For the evaluation of performance of the proposed method, we applied the XOR problem and numeral patterns classification The experimentation results showed that the proposed method has improved the performance compared to the conventional backpropagatiot the backpropagation with momentum, and the Jacob's delta-bar-delta method.

• Proceedings of the KAIS Fall Conference
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• 2010.11a
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• pp.341-343
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• 2010

The parameters of PID controller should be readjusted whenever system character change. In spite of a rapid development of control theory, this work needs much time and effort of expert. In this paper, to resolve this defect, after the sample of parameters in the changeable limits of system character is obtained, these parametrs are used as desired values of back propagation learning algorithm, also neural network auto tuner for PID controller is proposed by determing the optimum structure of neural network. Simulation results demonstrate that auto-tuning proper to system character can work well.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.361-364
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• 2002

In this paper, we propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is $Pad'{e}$-approximated, then initial values are determined by the Ziegler-Nickels method. So deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output, and has extent of applying without limit of K, L, T parameters.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.144-147
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• 2000

Controller refinement scheme to improve the performance of a conventional system automatically in frequency domain is proposed. The controller automatic tuning method features using experimental frequency responses of the conventional closed-loop system the conventional controller, and the improved closed-loop system, instead of poorly modeled plant due to non-linearities and disturbances. The improved closed-loop system characteristics is automatically acquired by the conventional closed-loop system characteristics and the proposed performance index in system bandwidth. And the proper controller is realized by least squares approximation in frequency domain. To testify the usefulness of the approach, the path tracking control of robot arm is performed. Experimental results and analytic results are well-matched.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.12 no.3
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• pp.7-13
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• 1998

In this paper, the control technique that ID controller are autotuned according to system dynamics, driving out sample in the changeable limits of system dynamics and learning neural network, is presented. In order to lean neural network, the backpropagation learning algorithm is used and the controller parameters obtained by rule-base are used as teacher's values. When load changes, the auto-tuning of PID controller proper to system dynamics is conformed by simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.36-42
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• 1996

In this paper, we proposed a PID controller, which could control unknown plants using Artificial Neural Network(ANN) for auto-tuning of the PID parameters. In the proposed algorithm, the parameters of the controller were adjusted to reduce the error of the controlled plant. In this process, the sensitivity between input and output of the unknown plant was needed. So, in order to obtain this sensitivity, the ANN's learnig ability was used. Computer simualtions were performed for the regulation problems, and the results were compared with those of Ziegler-Nichols PID controller. As a result, it was shown that the proposed algorithm outperformed Ziegler-Nichols controller in rise time, overshoot, undershoot, and setting time.