• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• Journal of Ocean Engineering and Technology
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• v.25 no.6
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• pp.1-8
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• 2011

This paper describes a new method for a digital gas metal arc welding (GMAW) system. The GMAW system is an arc welding process that incorporates the GMAW power source (PS-GMAW) with a wire feed unit (WFU). The PS-GMAW requires an electric power of constant voltage. A constant magnitude is maintained for the arc current by controlling the wire-feed speed of the WFU. A mathematical model is derived, and a self-tuning fuzzy proportional-integral-derivative (PID) controller is designed and applied to control the welding current. The electrode wire feeding mechanism with this controller is driven by a DC motor, which can compensate for both the molten part of the electrode and undesirable fluctuations in the arc length during the welding process. By accurately maintaining the output welding current and welding voltage at constant values during the welding process, excellent welding results can be obtained. Simulation and experimental results are shown to prove the effectiveness of the proposed controller.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1380-1384
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• 2015

The DC motor has the strong characteristics in the speed response, the system parameter variations and the external influence and is used as the speed controller with its good starting torque in the distributing industry. However development of the Microprocessor which is for high speed switching program can make better control system. This paper introduce to design of the high-effective DC motor controller that is using Software Bang-Bang Program of Fuzzy algorithm and to verify a PI controller and a Fuzzy controller.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1374-1376
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• 1996

In this paper We proposed a new method to generate fuzzy logic controllers through genetic algorithm(GA). In designing of fuzzy logic controllers encounters difficulties in the selection of optimized member-ship functions, gains and rule base, which is conventionally achieved by a tedious trial-and-error process. This paper develops genetic algorithms for automatic design of high performance fuzzy logic controllers which can overcome nonlinearities in many engineering control applications. The rule-base is coded in base-7 strings by generated from random function. Which can be presented in discrete fuzzy linguistic value, and using membership function with Gaussian curve. To verify the validity of this fuzzy logic controller it is compared with conventional fuzzy logic controller(FLC) and PID controller.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.12
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• pp.69-77
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• 1999

This paper describes the design of fuzzy digital PID controller using simplified indirect inference method. First, the fuzzy digital PID controller is derived from the conventional continuous time linear digital PID controller. Then the fuzzification, control-rule base, and defuzzification using SIM in the design of the fuzzy digital controller are discussed in detail. The resulting controller is a discrete time fuzzy version of the conventional digital PID controller, which has the same linear structure, but are nonlinear functions of the input signals. The proposed controller enhances the self-tuning control capability, particularly when the process to be controlled is nonlinear. When the SIM is applied, the fuzzy inference results can be calculated with splitting fuzzy variables into each action component and are determined as the functional form of corresponding variables. So the proposed method has the capability of the high speed inference and adapting with increasing the number of the fuzzy input variables easily. Computer simulation results have demonstrated the superior to the control performance of the one proposed by D. Misir et al.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.159-170
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• 1996

In this paper, we propose a generating method for the optimal rules for the nonlinear control system using evolution algorithms and fuzzy controller. With the aid of evolution algorithms optimal rules of fuzzy logic system can be automatic designed without human expert's priori experience and. knowledge. and ran be intelligent control. The approachpresented here generating rules by self-tuning the parameters of membership functions and searchs the optimal control rules based on a fitness value which Is tile defined performance criterion. Computer simulations demonstrates the usefulness of the proposed method In non -linear systems.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.191-193
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• 2005

This paper presents Hybrid PI controller of IPMSM drive using fuzzy adaptive mechanism(FAM) control. To increase the robustness, fixed gam PI controller, Hybrid PI controller proposes a new method based self tuning PI controller. Hybrid PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• The Journal of Information Technology
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• v.4 no.2
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• pp.117-127
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• 2001

A self-structured neural network algorithm that finds optimal fuzzy membership functions and nile base to fuzzy model is proposed and a fuzzy-neural network controller is designed to get more accurate position and velocity control of wheeled mobile robot. This procedure that is composed of three steps has its own unique process at each step. The elements of output term set are increased at first step and then the rule base Is varied according to increase of the elements. The adjusted controller is in competition with controller which doesn't include any increased elements. The adjusted controller will be removed if the control-law lost. Otherwise, the controller is replaced with the adjusted system. After finished regulation of output term set and rule base, searching for input membership functions is processed with constraints and fine tuning of output membership functions is done.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.32-34
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• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good Performance over a wide range of operation, even under ideal field oriented conditions. This paper is proposed model reference adaptive fuzzy control(MFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaption mechanism(FAM), MFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, MFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.58-69
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• 1995

In this paper GFI (Generalized Fuzzy Isodata) and FI (Fuzzy Isodata) algorithms are studied and applied to the tire tread pattern classification problem. GFI algorithm which repeatedly grouping the partitioned cluster depending on the fuzzy partition matrix is general form of GI algorithm. In the constructing the binary tree using GFI algorithm cluster validity, namely, whether partitioned cluster is feasible or not is checked and construction of the binary tree is obtained by FDH clustering algorithm. These algorithms show the good performance in selecting the prototypes of each patterns and classifying patterns. Directions of edge in the preprocessed image of tire tread pattern are selected as features of pattern. These features are thought to have useful information which well represents the characteristics of patterns.