• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.2
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• pp.142-149
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• 2022

In increasing the safety and usage of lithium-ion battery packs, reducing the parameter deviation between cells, such as voltage and temperature within the battery pack, is important. In this study, we propose a screening method to reduce parameter deviation between cells in battery packs. Screening algorithms are constructed based on Fuzzy logic and quantitatively express the similarities between battery cells. Screening is applied by utilizing series resistance components after experiments of electrical characteristics that consider the operation status of battery packs. After screening, the standard deviation of series resistance components according to the similarity ranking is compared and analyzed, and their conformity are verified with the algorithm parameters.

• Proceedings of the Safety Management and Science Conference
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• 2000.05a
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• pp.111-123
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• 2000

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences. Recycling cells are formed considering design, process and usage attributes. In this paper, a novel approach to the design of cellular recycling system is proposed, which deals with the recycling cell formation and assignment of identical products concurrently. Fuzzy clustering algorithm and Fuzzy-ART neural network are applied to describe the states of disposal product with the membership functions and to make recycling cell formation. This approach leads to recycling and reuse of the materials, components, and subassemblies and can evaluate the value at each cell of disposal products. Application examples are illustrated by disposal refrigerators, compared fuzzy clustering with Fuzzy-ART neural network performance in cell formation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.680-683
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• 1996

The dynamics of the vehicle system has highly nonlinear components such as an engine, a torque converter and variable road condition. This thesis proposes a Fuzzy Logic Algorithm that shows better control performance than Antiwindup PI in the highly nonlinear vehicle system. Traction Control System(TCS), which adjusts throttle valve opening by Fuzzy Logic Algorithm improves vehicle drivability, steerability and stability when vehicle is starting and cornering. When a throttle valve is opened at large degree, Fuzzy Logic Algorithm shows better performances like a small settling time and a small oscillation than Antiwindup PI in simulation. The decreased desired slip ratio improves steerability in the simulation when a vehicle is cornering. The Fuzzy Logic Algorithm has been tested by a 1/5-scale vehicle for tracking the constant desired velocity.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.109.6-109
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• 2002

In this paper, the scheme of fuzzy system construction using GA(genetic algorithm) and FCM(Fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. in the structure identification, input data is trans-formed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, the number of fuzzy rule is obtained by a given performance criterion. In the parameter identification, the premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this, one can systematically obtain optimal parameter and the v..

• Journal of the Korean Society of Marine Environment & Safety
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• v.2 no.1
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• pp.89-95
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• 1996

This paper describes a fuzzy controlled pre-chlorination technique for purifying the pulluted raw water in water purification lants. For the purpose of obtaining the high quality water, the appropriate pre-chlorine dosage rate has to be continuously adjusted according to a change in quality of a intake raw water, weather, solar nergy mount, temperature and etc. Therefore, the method of expressing an expert's empirical knowledge cumulated from his past carrier by fuzzy reasoning and the fuzzy controller design technique is necessary.In this paper fuzzy membership functions and rules accordingto emprircal knowledge and experimental field data were obtained, And also fuzzy cintriller design using four feedforward components for the determination of pre-chlorine dosage rate and four feedback ones for the compensation of its dosage rate with residual chlorine and its change rate, was executed.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.338-341
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• 1994

This paper presents a Fuzzy-PID controller based on Fuzzy logic. Up to now PID controller has had the difficulty of obtaining the optimal gain, and Fuzzy controller has had the difficulty of determining scale factor affecting the performance of control. So that a Fuzzy-PID controller is presented here self tuning of the scale factor and optimal gain. The results of simulation show a good performance in comparison with Ziegler-Nichols controller, having the generality of determining the components of scale factor in Fuzzy rule.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.409-416
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• 2004

An active modal-fuzzy control method using hydraulic actuators is presented for seismic response reduction. In the proposed control system, a new fuzzy controller designed in the modal space produces the desired active control force. This type controller has all advantages of the fuzzy control algorithm and modal approach. Since it is very difficult to select input variables used in fuzzy controller among an amount of state variables in the active fuzzy control system the presented algorithm adopts the modal control algorithm which is able to consider more easily information of all state variables in civil structures that are usually dominated by first few modes. In other words, all information of the whole structure can be considered in the control algorithm evaluated to reduce seismic responses and it can be efficient for especially civil structures. In addition, the presented algorithm is expected to magnify utility and performance caused by efficiency that the fuzzy algorithm can handle complex model more easily. An active modal-fuzzy control scheme is applied together with a Kalman filter and a low-pass filter to be applicable to real civil structures. A Kalman filter is considered to estimate modal states and a low-pass filter was used to eliminate spillover problem. The results of the numerical simulations far a wide amplitude range o f loading conditions and for historic earthquakes having various frequency components show that the proposed active modal-fuzzy control system can be beneficial in reducing seismic responses of civil structures.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.754-759
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• 2001

In this paper, we propose a TSK(Takagi-Sugeno-Kang)-type fuzzy classifier using PCA(Principal Component Analysis), FCM(Fuzzy c-Means) clustering, ANFIS(Adaptive Neuro-Fuzzy Inference System) and hybrid GA(Genetic Algorithm). First, input data is transformed to reduce correlation among the data components by PCA. FCM clustering is applied to obtain a initial TSK-type fuzzy classifier. Parameter identification is performed by AGA(Adaptive GA) and RLSE(Recursive Least Square Estimate). Finally, we applied the proposed method to Iris data classificationl problems and obtained a better performance than previous works.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.104-111
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• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1093-1102
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• 2010

Principal component analysis (PCA) is a well-known method for dimension reduction while maintaining most of the variation in data. Although PCA has been applied to many areas successfully, it is sensitive to outliers. Several variants of PCA have been proposed to resolve the problem and, among the variants, robust fuzzy PCA (RF-PCA) demonstrated promising results. RF-PCA uses fuzzy memberships to reduce the noise sensitivity. However, there are also problems in RF-PCA and the convergence property is one of them. RF-PCA uses two different objective functions to update memberships and principal components, which is the main reason of the lack of convergence property. The difference between two functions also slows the convergence and deteriorates the solutions of RF-PCA. In this paper, a variant of RF-PCA, called RF-PCA2, is proposed. RF-PCA2 uses an integrated objective function both for memberships and principal components. By using alternating optimization, RF-PCA2 is guaranteed to converge on a local optimum. Furthermore, RF-PCA2 converges faster than RF-PCA and the solutions found are more similar to the desired solutions than those of RF-PCA. Experimental results also support this.