• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.243-244
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• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in order to increase an output of the PV array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.1254-1263
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• 1993

Representing knowledge uncertainty , aggregating evidence confidences , and propagation uncertainties are three key elements that effect the ability of a rule-based expert system to represent domains with uncertainty . Fuzzy set theory provide a good mathematical tool for representing the vagueness associated with a variable when , as the condition of a rule , it only partially corresponds to the input data. However, the aggregation of ANDed and Ored confidences is not as simple as the intersection and union operators defined for fuzzy set membership. There is, in fact, a certain degree of compensation that occurs when an expert aggregates confidences associated with compound evidence . Further, expert often consider individual evidences to be varying importance , or weight , in their support for a conclusion. This paper presents a flexible approach for evaluating evidence and conclusion confidences. Evidences may be represented as fuzzy or nonfuzzy variables with as associat d degree of certainty . different weight can also be associated degree of certainty. Different weights can also be assigned to the individual condition in determining the confidence of compound evidence . Conclusion confidence is calculated using a modified approach combining the evidence confidence and a rule strength. The techniques developed offer a flexible framework for representing knowledge and propagating uncertainties. This framework has the potention to reflect human aggregation of uncertain information more accurately than simple minimum and maximum operator do.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.4
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• pp.159-164
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• 2008

In diesel engine technology the drive to reduce emissions and fuel consumption with improved performance targets has led to many advances. In particular, Exhaust Gas Recirculation (EGR) and Variable Geometry Turbocharger (VGT) have played a key role in achieving these aims by permitting flexible control of the engine inlet gas charge. The full potential of these devices are difficult to achieve due to limitations in the classical control methods. However, fuzzy logic is particularly appealing due to its simple heuristic nature. The controller used in this work was designed using the Matlab Fuzzy Logic Toolbox. The overall object is to access the potential for emissions and fuel consumption reductions during transient events whilst maintaining and even improving driveability. Classical control methods (PID), as used on production engines, are examined and contrasted with an coordinated control that utilizes fuzzy logic.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.501-503
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• 1999

In this paper, the design method of a hybrid fuzzy controller with an optimal auto-tuning method is proposed. The conventional PID controller becomes so sensitive to the control environments and the change of parameters that the efficiency of its utility for the complex and nonlinear plant has been questioned in transient state. In this paper, first, a hybrid fuzzy logic controller(HFLC) is proposed. The control input of the system in the HFLC is a convex combination by a fuzzy variable of the FLC's output in transient state and the PID's output in steady state. Second, a powerful auto-tuning algorithm is presented to automatically improve the Performance of controller, utilizing the improved complex method and the genetic algorithm. The algorithm estimates automatically the optimal values of scaling factors and PID coefficients. Controllers are applied to the plants with time-delay and the DC servo motor Computer simulations are conducted at the step input and the system performances are evaluated in the ITAE.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.839-845
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• 2013

A CSTR (Continuous Stirred Tank Reactor) is a highly nonlinear process with varying parameters during operation. Therefore, tuning of the controller and determining the transition policy of controller parameters are required to guarantee the best performance of the CSTR for overall operating regions. In this paper, a methodology employing the 2DOF (Two-Degree-of-Freedom) PID controller, the anti-windup technique and a fuzzy gain scheduler is presented for the temperature control of the CSTR. First, both a local model and an EA (Evolutionary Algorithm) are used to tune the optimal controller parameters at each operating region by minimizing the IAE (Integral of Absolute Error). Then, a set of controller parameters are expressed as functions of the gain scheduling variable. Those functions are implemented using a set of "if-then" fuzzy rules, which is of Sugeno's form. Simulation works for reference tracking, disturbance rejecting and noise rejecting performances show the feasibility of using the proposed method.

• Journal of Electrical Engineering and Technology
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• v.3 no.4
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• pp.520-527
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• 2008

This work focuses on the evaluation of active power filter which is controlled by fuzzy logic and neural network based controller for harmonic mitigation and power factor enhancement. The APF consists of a variable DC voltage source and a DC/AC inverter. The task of an APF is to make the line current waveform as close as possible to a sinusoid in phase with the line voltage by injecting the compensation current. The compensation current is estimated using adaptive neural network. Using the estimated current, the proposed APF is controlled using neural network and fuzzy logic. Computer simulations of the proposed APF are performed using MATLAB. The results show that the proposed techniques for the evaluation of APF can reduce the total harmonic distortion less than 3% and improve the power factor of the system to almost unity.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.7
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• pp.29-40
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• 2009

This paper proposes a modeling and controller design approach for a hybrid wind power generation system that considers a fixed wind-turbine and a dump load. Since operating conditions are kept changing, it is challenge to design a control for reliable operation of the overall system To consider variable operating conditions, Takagi-Sugeno (TS) fuzzy model is taken into account to represent time-varying system by expressing the local dynamics of a nonlinear system through sub-systems, partitioned by linguistic rules. Also, each fuzzy model has uncertainty. Thus, in this paper, a modem nonlinear control design technique, the sliding mode nonlinear control design, is utilized for robust control mechanism In the simulation study, the proposed controller is compared with a proportional-integral (PI) controller. Simulation results show that the proposed controller is more effective against disturbances caused by wind speed and load variation than the PI controller, and thus it contributes to a better quality wind-hybrid power generation system.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.3
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• pp.32-48
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• 1994

This paper proposes the compensation algorithm of conventional shift pattern using fuzzy reasoning in automatic transmission vehicles. Recently, automatic transimssion vehicles are continually increasing because of theire ease to drive. Also users require the high performance which includes the smooth shift quality and shift scheduling that matches driver;s intentions. So the shift scheduling has been inproved significantly through the application of electronic control. But, in spite of this development, vehicles using conventional shift pattern are sometimes in discord with driver's intention on roads. In this paper, the paper, the proposed compensation algorithm makes a automatic transmission vehicle be able to select an optimal gear shifting time and position using fuzzy reasoning and make a vehicle driver feel confortable even when the vehicle runs on roads which is extremely changed. Therefore, a vehicle driver can expect to reduce the nimber of unnecessary gear shifting and expect the fuel efficiency high. To show usefulness of the proposed method, some simulation are made to compared with conventional gear shifting. Paper prosposes the compensation mehtod of conventional shift pattern using fuzzy reasoning for the purpose that a vehicle can select an optimal gerar shifting time and position in automatic vehicle. Though the conventional shift pattern has no pliability, vehicle driver can feel comfortable and can reduce the number of unnecessary gear shifting using the proposed method on variable road condition. Therefore, it can be expected the fuel efficiency.

• Journal of Power Electronics
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• v.11 no.6
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• pp.914-921
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• 2011

Commencing with incandescent light bulbs, every load today creates harmonics. Unfortunately, these loads vary with respect to their amount of harmonic content and their response to problems caused by harmonics. The prevalent difficulties with harmonics are voltage and current waveform distortions. In addition, Electronic equipment like computers, battery chargers, electronic ballasts, variable frequency drives, and switching mode power supplies generate perilous amounts of harmonics. Issues related to harmonics are of a greater concern to engineers and building designers because they do more than just distort voltage waveforms, they can overheat the building wiring, cause nuisance tripping, overheat transformer units, and cause random end-user equipment failures. Thus power quality is becoming more and more serious with each passing day. As a result, active power filters (APFs) have gained a lot of attention due to their excellent harmonic compensation. However, the performance of the active filters seems to have contradictions with different control techniques. The main objective of this paper is to analyze shunt active filters with fuzzy and pi controllers. To carry out this analysis, active and reactive current methods ($i_d-i_q$) are considered. Extensive simulations were carried out. The simulations were performed under balance, unbalanced and non sinusoidal conditions. The results validate the dynamic behavior of fuzzy logic controllers over PI controllers.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.8 no.1
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• pp.53-56
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• 1994

PID controller is being used in many servo control systems. However, when a control system has disturbance or time variable characteristic, it is very difficult to guarantee the robustness of the system. In the way of solving this problem, in this paper, a control method using the PID controller with Fuzzy Logic Regulator is presented. Fuzzy Logic Regulator is designed by error and error change, the kth sampling control input is decided by the addition of the kth sampling defuzzification value and the (k-l)th sampling defuzzification value. Control input is transmitted to input. The robust control function of Fuzzy Logic Regulator is demonstrated by the computer simulation.