• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2000.11a
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• pp.193-198
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• 2000

Switched reluctance motor drives have been finding their applications in the variable speed drives due to their relatively low cost, simple and robust structure, controllability and high efficiency. Fuzzy control does not need any model of plant. It is based on plant operator experience and heuristics. Fuzzy control is basically adaptive and gives robust performance for plant parameter variation. This paper deals with the sped control of switched reluctance motor using fuzzy controller with 7-rule based fuzzy logic. The proposed fuzzy controller is superior to the control performance of the conventional PI controller. The fuzzy controller is implemented by 80C196KC, 16 bit one-chip microcontroller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1207-1210
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• 1993

There is an opinion of regarding a simple fuzzy logic controller as a kind of Variable Structure Controller in recent years. The opinion may provide an analytical basis which describes the robustness to uncertainty and the stability of a fuzzy logic controller. So in this paper, a fuzzy logic controller based on the Variable Structure System with is designed for a robot manipulator which is a class of complex, nonlinear system with uncertainty. Fuzzy control rules, membership shape of the I/O variables of the fuzzy logic controller are designed for guaranteeing the stability of an overall control system. From a computer simulation of dynamic control of a two link robot manipulator, the design procedure of the fuzzy logic controller is validated.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.8
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• pp.2088-2100
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• 1994

Considerable attention has been given to controller designs that utilize the variable structure system theory in order to achieve robust tracking performance of robotic manipulators subjected to parameter variations and extraneous disturbances. However, the theory has not had wide spread acceptance in practical control engineering community due mainly to the worry of chattering which is inherently ever-existing in the variable structure system. This paper presents a novel type of fuzzy-sliding mode controller to alleviate the chattering problem. A sliding mode controller for robust robot control is firstly synthesized with an assumption that the imposed system uncertainties satisfy matching conditions so that certain deterministic performances can parameters and control rules are obtained from a relation between predetermined sliding surfaces and representative points in the error state space. A two degree-of-freedom robotic manipulator subjected to a variable payload and a torque disturbance is considered in order to demonstrate superior tracking performance accrued from the proposed methodology.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.144-150
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• 1999

n active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. The result of simulations shows that the crane is just controlled for a very large swing angle of 1 radian within nearly one cycle.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.680-688
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• 2001

In this paper, the fuzzy control with variable input gain is applied to maintain the consistent tension in the process of taking up and releasing texture. In the process of discharging web on one side rolling it on another, the take-up drum gets smaller on the release drum side as it gets bigger on the rolling side, thus it is necessary to change the balance of velocity between the sides. In order to solve the problem a tension controller is necessary. The PI control method has been employed to maintain the consistent tension, but the PI control method produces a problem which requires an experienced worker with the traits of the machine, in order to perform the fine adjustments according to the environment of the process. For solving the above problem, we apply fuzzy control to the tension system, in order to produce a uniform roll. For the performance test, the fuzzy controller does not need to revise the parameters. Therefore the fuzzy controller exhibits an excellent additivity for the tension system where the system is changed with time.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.6-8
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• 2005

In this paper, we discuss model identification of nonlinear data using GAs-based Fuzzy Polynomial Neural Networks(GAs-FPNN). Fuzzy Polynomial Neural Networks(FPNN) is proposed model based Group Method Data Handling(GMDH) and Neural Networks(NNs). Each node of FPNN is expressed Fuzzy Polynomial Neuron(FPN). Network structure of nonlinear data is created using Genetic Algorithms(GAs) of optimal search method. Accordingly, GAs-FPNN have more inflexible than the existing models (in)from structure selecting. The proposed model select and identify its for optimal search of Genetic Algorithms that are no. of input variables, input variable numbers and consequence structures. The GAs-FPNN model is select tuning to input variable number, number of input variable and the last part structure through optimal search of Genetic Algorithms. It is shown that nonlinear data model design using Genetic Algorithms based FPNN is more usefulness and effectiveness than the existing models.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.452-461
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• 2007

Adaptive anti-sway and trajectory tracking control of overhead crane is presented, which utilizes Fuzzy Uncertainty Observer(FUO) and Fuzzy based Variable Structure Control(FVSC). We consider an overhead crane system which can be decoupled into the actuated and unactuated subsystems with its own lumped uncertainty such as parameter uncertainties and external disturbance. First, a new method for anti-sway control using FVSC is proposed to improve the conventional method based on Lyapunov direct method, while a conventional trajectory tracking control law using feedback linearization is directly adopted. Second, FUO is designed to estimate one of the two lumped uncertainties which can compensate both of them, based on the fact that two lumped uncertainties are coupled with each other. Then, an adaptive anti-sway control is proposed by incorporating the proposed FVSC and FUO. Under the condition that the observation error is Uniformly Ultimately Bounded(UUB) within an arbitrarily shrinkable region, the overall closed-loop system is shown to be Globally Uniformly Ultimately Bounded(GUUB). In addition, the Global Asymptotic Stability(GAS) of it is shown under the vanishing disturbance assumption. Finally, the effectiveness of the proposed scheme has been confirmed by numerical simulations.

• Journal of Power System Engineering
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• v.22 no.1
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• pp.18-24
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• 2018

This paper focuses on systematic design about the membership ranges of the main design factors such as control error, control error rate, and sampling time for the fuzzy logic control of the variable speed drive refrigeration cycle. The upper and the lowest limit of the membership ranges are set up from the data of static characteristics obtained by experiments. Three kinds of membership ranges on the control error and the control error rate are tested by experiments. Especially, an effect of sampling time on control performance is also investigated in the same way. Experimental data showed the control error rate and the sampling time strongly effected on the control performance of the refrigeration cycle with a variable speed drive.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.5
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• pp.66-75
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• 1997

A fault diagnosis system for a variable speed rotating shaft probably demands a huge database, which makes it diffcult to be realized. This stuydy presents an effective method of fault diagnosis for variable speed rotating shafts. The proposed method is based upon a fuzzy reasoning and it includes a stepwize strategy to reduce the size of database in a diagnosis system. A computer program is developed to show the procedure of the diagnosis, and four cases of faults are applied to the program to illustarate the effectiveness of the proposed method. The propsed method is found to be useful in reducing the size of database from observation of the data files of the dianosis system. The case studies show that the proposed method can be useful for the diagnosis of variable speed rotating shafts.

• Journal of applied mathematics & informatics
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• v.34 no.3_4
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• pp.355-357
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• 2016

Recently, some results of Blackwell's Theorem in which interarrival times are characterized as fuzzy variables under t-norm-based fuzzy operations are discussed by Hong. However, these results are invalid. In this note, we give counter examples of these results.