• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.597-605
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• 2012

Evidence framework enables us to determine the tuning constant in a penalized likelihood formula. We apply the framework to the estimating parameters of normal mixtures. Evidence, which is a solely data-dependent measure, can be evaluated by Laplace approximation. According to a synthetic data simulation, we found that the proper values of the tuning constant can be systematically obtained.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1173-1177
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• 2006

Using an inner P controller, a tuning rule useful for processes with wide ratios of time delay over time constant is proposed. Internal model control method and pole assignment method are utilized. It can be used for processes with wide range of the ratio of time delay to time constant without incovenience to choose different tuning rules.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.7
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• pp.696-705
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• 1991

This paper describes the procedures for pre-tuning and re-tuning the gains of PI controller based on output patterns -output error integral- of the unknown process which may not have any information, for example, system order, deadtime, time constant, etc. The key ideas of the proposed adaptive scheme are as follows. The scheme determines the initial gains by using ZNM (Ziegler-Nichols Method) with relay feedback, and then the adaptive algorithms by pattern recognition are introduced for re-runing the PI gains with on-line scheme whenever control conditions are changed. Because, among the various auto-tuning procedures, ANM with relay feedback has the difficulty in re-tuning with on-line and Bristol method has no comment on initial settings and has variables to pre-determine, which makes the algorithm comples, the proposed methods have the combined scheme with above two procedures to recover those problems. And this paper proposes a simple way to determine adaptive constant in Bristol method. To show the validity of the proposed method, an example is illustrated by computer simulation and a laboratory process, heat exchanger, is experimented.

• Journal of Sensor Science and Technology
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• v.6 no.2
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• pp.115-122
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• 1997

In this paper, on-chp atomatic tuning circuit, using proposed integration level approximation technique, is designed to tuning of the variation of RC time-constant due to aging or temperature variation, etc. This circuit reduces the error, the difference between code values and real outputs of integrator, which is drawback of presented dual-slope tuning circuit and eliminates modulations of processing signals in integrated circuit due to fixed tuning codes during ordinary operation. This system is made up of simple integrator, A/D converter and digital control circuit and all capacitors are replaced by programed capacitor arrays in this system. This tuning circuit with 4 bit resolution achieves $-9.74{\sim}+9.68%$ of RC time constant error for 50% resistance variation.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.40-44
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• 2002

In this paper, robust control method using fuzzy PI parameter tuning is proposed to control constant thrust force on load variation. First, a structure and thrust force equations of the LPM are described. Second, an controller with PI parameter-tuning using a fuzzy theory is proposed to achieve high-precision position with constant thrust force of the LPM. Finally, the effectiveness of an fuzzy PI controller is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line Fuzzy PI gain tuning method with regard parametric variations and load thrust force variations.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.744-748
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• 1989

A newly developed Expert System (ES) for the tuning of thermal power plant control equipment is described. The system is furnished with the rules for controller tuning which were obtained by analysis and arranging the data and knowledge from the experts or tuning records. Based on these rules, automatic tuning or setting of the control parameters is performed in real-time base. The performance of the test equipment, a combination of ES and a boiler simulator, was examined in the automatic tuning test for steam pressure, steam temperature, and load controllers of a constant-pressure once-through boiler model. It was confirmed from the test results that the system is quite promising for future application to actual plants, since the tuning results obtained by the proposed system were similar to those by tuning experts.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.538-548
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• 2016

The purpose of this study is to identify the possibility of effective tuning works, understand the characteristics of tuning engine, and analyse the basic data of engine tuning inspection corresponding to the safe operation and environment of a driving gasoline car. The effects of tuning on the characteristics of performance and exhaust emissions under a wide range of engine speeds are experimentally investigated by the actual driving car with a four-cycle, four-cylinder DOHC, turbo-intercooler, water-cooled gasoline engine operating at four types of non-tuning, tuning 1, 2 and 3. The tuning parts in the gasoline engine are the intake manifold, intake pipe and air filter. In the experiment, the output, torque and air-fuel ratio of the five-speed automatic transmission vehicles were measured at the chassis dynamometer(Dynojet 224xLC) with one person on board. The exhaust emissions of $NO_X$, THC, CO, $O_2$ and $CO_2$, and excess air ratio(${\lambda}$) at the other chassis dynamometer(DASAN-MD-ASM-97-KR-HD) were also measured by the idle/constant-speed mode(ASM2525 mode) test method. It is found that the actual air-fuel ratios of non-tuning and tuning engines were shown to be lower than the stoichiometric air-fuel ratio with increasing engine speed, and the actual air-fuel ratio of non-tuning engine was slightly higher than those of tuning engines when the engine speed is more than 4000 rpm. The output was significantly increased by the tuning whereby the maximum output of tuning engine was more increased to approximately 117.64% than that of non-tuning engine. In addition, CO, THC and $NO_X$ emissions of non-tuning and tuning engines measured by the constant-speed test mode were all satisfied with the inspection standards. CO emission was increased, while THC and $NO_X$ emissions were reduced by tuning.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.430-433
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• 1988

An adaptive control system for D.C servo drive is developed via minimum variance control theory. The problem of designing this controller under varying load conditions is discussed. A robust self tuning controller that can track a constant reference and reject constant load disturbance is developed. Simulation study shows that the controller has excellent adaptation, capability as well as transient recovery under load changes.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.295-298
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• 1996

In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.160-168
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• 1997

A $H_{\infty}$self-tuning control scheme for the tip position of a flexible link robot handling unknown loads is presented here. The scheme essentially comprises a recursive least-squares identification algorithm and $H_{\infty}$self-tunning controller. The $H_{\infty}$control low is designed to be robust to uncertain parameters and the self-tunning action provides adaption to unknown parameters. Through numerical study, the performance comparison of the $H_{\infty}$self-tuning controller with a constant gain $H_{\infty}$controller as well as a LQG self-tuning controller clearly shows its superior ability in handling load changes in quiescent states.nt states.