• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.4
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• pp.188-195
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• 2002

We proposed the design of SVC adaptive fuzzy logic controller(AFLC) using Tabu search and neural network. We tuned the gains of input-output variables of fuzzy logic controller(FLC) and weights of neural network using Tabu search. Neural network was used for adaptively tuning the output gain of FLC. The weights of neural network was learned from the back propagation algorithm in real-time. To evaluate the usefulness of AFLC, we applied the proposed method to single-machine infinite system. AFLC showed the better control performance than PD controller and GAFLS[10] for three-phase fault in nominal load which had used when tuning AFLC. To show the robustness of AFLC, we applied the proposed method to disturbances such as three-phase fault in heavy and light load. AFLC showed the better robustness than PD controller and GAFLC[10].

• Journal of Biosystems Engineering
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• v.21 no.2
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• pp.167-174
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• 1996

A Fuzzy Logic Controller(FLC) was developed for the autonomous operation of speedsprayer in an orchard. The autonomous operation with the FLC was graphically simulated under the real condition of the orchard. Image processing was used to find out the direction of running and four ultrasonic sensors were used to detect obstacles for the running. The simulation results showed that the speedsprayer could be operated autonomously with the FLC combined with the image processing and the ultrasonic sensors.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.47-51
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• 2001

According as the controlled plants become more complex and large-scaled, the development of more intelligent control schemes is required in the control field. A fuzzy logic control (FLC) is one of proper schemes for this tendency. Recently, fuzzy control has been applied successfully to many industrial applications due to a number of advantages. But it still has some disadvantages. The conventional FLC has many tuning parameters: membership functions, scaling factors, and so forth. In order to improve this problem, a single-input fuzzy logic control (SFIC) which greatly simplifies the design process of the conventional FLC was proposed. Many research has also been proposed to develop the stability analysis of the FLC. In this paper we analyze the absolute stability of the SFLC. We first expand a nonlinear controlled plant into a Taylor series about a nominal operating point. And a fuzzy control system is transformed into a Lure system with nonlinearities. We also prove that the closed-loop system with the SFLC satisfies the sector condition globally.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.994-997
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• 2003

This Paper presents a study of the performance of a DC servo motor with a model reference adaptive fuzzy speed controller (MRAFSC) in the presences of load disturbances. MRAFSC comprised inner feedback loop consisting of the fuzzy logic controller (FLC) and plant, and outer loop consisting of an adaptation mechanism which is designed for tuning a control rule of the FLC. Experimental results show the good performance in the DC servo motor system with the proposed adaptive fuzzy controller.

• Journal of Power Electronics
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• v.11 no.4
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• pp.542-550
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• 2011

This paper describes the design and hardware implementation of a Single Input Fuzzy Logic Controller (SIFLC) to regulate the output voltage of a boost power converter. The proposed controller is derived from the signed distance method, which reduces a multi-input conventional Fuzzy Logic Controller (CFLC) to a single input FLC. This allows the rule table to be approximated to a one-dimensional piecewise linear control surface. A MATLAB simulation demonstrated that the performance of a boost converter is identical when subjected to the SIFLC or a CFLC. However, the SIFLC requires nearly an order of magnitude less time to execute its algorithm. Therefore the former can replace the latter with no significant degradation in performance. To validate the feasibility of the SIFLC, a 50W boost converter prototype is built. The SIFLC algorithm is implemented using an Altera FPGA. It was found that the SIFLC with asymmetrical membership functions exhibits an excellent response to load and input reference changes.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2258-2263
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• 2003

This paper presents the design and development of an optimal fuzzy logic controller (FLC) for a laser tracking system. An optimal intelligent fuzzy logic controller was founded on integral criterion of the fuzzy models and three-dimensional fuzzy control. Research had been also concentrated on the methods for multivariable fuzzy models for the purposes of real-time process. Simulation results have shown remarkable tracking performance of this fuzzy PID controller.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.76-86
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• 2002

In this paper, we suggest a hybrid genetic algorithm reinforced by a fuzzy logic controller (flc-HGA) to overcome weaknesses of conventional genetic algorithms: the problem of parameter fine-tuning, the lack of local search ability, and the convergence speed in searching process. In the proposed flc-HGA, a fuzzy logic controller is used to adaptively regulate the fine-tuning structure of genetic algorithm (GA) parameters and a local search technique is applied to find a better solution in GA loop. In numerical examples, we apply the proposed algorithm to a simple test problem and two complex combinatorial optimization problems. Experiment results show that the proposed algorithm outperforms conventional GAs and heuristics.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.265-271
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• 1997

A fuzzy logic controller (FLC) has been widely used for many applications in recent years. But the relationship between control performance and design parameters has not been handled explicity in the conventional theory of fuzzy logic control. In this paper, based on the similarity between an FLC and a variable structure control (VSC) theory, a performance evaluation of an FLC, which gives quantitative accounts on the relationship is presented. The validity of the analysis is verified through extensive computer simulations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.1-9
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• 1996

Although the fuzzy logic controller (FLC) has been adopted in many engineering applications, one hesitates to adopt the FLC in critical applications, since there was no definite control theoretic analysis. In this paper, based on the stability/robustness analysis of an FLC by S.Y.Yi$^{[3]}$, we apply the FLC to robot manipulator with the structured and unstructured uncertainties e.g., load variation and firction, etc. And we verify the performance of the FLC by computer simulation on a simple two-link robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1183-1187
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• 1993

The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment a noble FLC is proposed, which is based on simple control rules while offering easy tuning of control parameters by utilizing real operation characteristics of an operator. The proposed FLC consists of two parts, the proportional controller part and the FLC part. Experiments are carried out on a test bed which is built around a commercial excavator. The controller is applied to bhe leveling of excavator's bucket tip, which is one of the main functions in an excavator's operation.