• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2702-2704
• /
• 2001

In this Letter, we propose a comprehensive design methodology of hybri'd Fuzzy controllers (HFC). The HFC comes as a form of a convex combination of a standard PID controller and a fuzzy controller. The design procedure dwells on the use of evolutionary computing (genetic algorithm) and an auto-tuning algorithm. The tuning of the scaling factors of the HFC is an essential component of the entire optimization process. A numerical study is presented and a detailed comparative analysis is also included.

• Journal of Biomedical Engineering Research
• /
• v.22 no.3
• /
• pp.217-222
• /
• 2001

This paper proposes the new method based on fuzzy logic which recognizes between normal, and abnormal(two types of abnormal : follicular neoplastic, and papillary neoplastic) of thyroid gland cells from pre-obtained 16 feature parameters of image data. This paper applies the genetic algorithms to obtain the dominant feature parameters which have a great influence on discrimination between normal and abnormal cells. This paper shows the effectiveness of proposed method to 240 thyroid gland cells(60 normal cells, 120 follicular neoplastic cells and 60 papillary neoplastic cells) and new dominant feature parameters obtained by genetic algorithms. As a consequence of using the proposed method, average recognition rate of 88.75 % was obtained.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.5
• /
• pp.598-603
• /
• 2004

An optical head actuator of an optical disk drive consists of two servo mechanisms for the focusing and the tracking to acquire data from disk. As the rotational speed of the disk grows, the utilized lag-lead-lead compensator has known to be above its ability for precisely controlling the optical head actuator. To overcome the difficulty, this paper propose a new controller design method for optical head actuator based fuzzy proportional-integral-derivative (PID) control and the genetic algorithm(GA). It employs a two-stage control structure with a fuzzy PI and a fuzzy PD control and is optimized by the GA to yield the suboptimal fuzzy PID control performance. It is shown the feasibility of the proposed method through a numerical tracking actuator simulation.

• Earthquakes and Structures
• /
• v.22 no.1
• /
• pp.53-64
• /
• 2022

This study proposes an intelligent semi-active isolation system combining a variable-stiffness control device and ground motion characteristic prediction. To determine the optimal control parameter in real-time, a genetic algorithm (GA)-fuzzy control law was developed in this study. Data on various types of ground motions were collected, and the ground motion characteristics were quantified to derive a near-fault (NF) characteristic ratio by employing an on-site earthquake early warning system. On the basis of the peak ground acceleration (PGA) and the derived NF ratio, a fuzzy inference system (FIS) was developed. The control parameters were optimized using a GA. To support continuity under near-fault and far-field ground motions, the optimal control parameter was linked with the predicted PGA and NF ratio through the FIS. The GA-fuzzy law was then compared with other control laws to verify its effectiveness. The results revealed that the GA-fuzzy control law could reliably predict different ground motion characteristics for real-time control because of the high sensitivity of its control parameter to the ground motion characteristics. Even under near-fault and far-field ground motions, the GA-fuzzy control law outperformed the FPEEA control law in terms of controlling the isolation layer displacement and the superstructure acceleration.

• KIEE International Transactions on Power Engineering
• /
• v.3A no.4
• /
• pp.181-190
• /
• 2003

This paper presents the design of a fuzzy power system stabilizer (FPSS) using an adaptive evolutionary algorithm (AEA). AEA consists of genetic algorithm (GA) for a global search capability and evolution strategy (ES) for a local search in an adaptive manner when the present generation evolves into the next generation. AEA is used to optimize the membership functions and scaling factors of the FPSS. To evaluate the usefulness of the FPSS, we applied it to a single-machine infinite bus system (SIBS) and a power system simulator at the Korea Electrotechnology Research Institute. The FPSS displays better control performance than the conventional power system stabilizer (CPSS) for a three-phase fault in heavy load, which is used when tuning FPSS. To show the robustness of the FPSS, it is applied with disturbances such as change of mechanical torque and three-phase fault in nominal and heavy load, etc. The FPSS also demonstrates better robustness than the CPSS. Experimental results indicate that the FPSS has good system damping under various disturbances such as one-line to ground faults, line parameter changes, transformer tap changes, etc.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.442-445
• /
• 1997

We present a hybrid self-tuning method of fuzzy inference systems with hyper elliptic Gaussian membership functions using genetic algorithm(GA) and back-propagation algorithm. The proposed self-tuning method has two phases : one is the coarse tuning process based on GA and the other is the fine tuning process based on back-propagation. But the parameters which is obtained by a GA are near optimal solutions. In order to solve the problem in GA applications, it uses a back-propagation algorithm, which is one of learning algorithms in neural networks, to finely tune the parameters obtained by a GA. We provide Box-Jenkins time series to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1871-1875
• /
• 1997

Crane operation is manually accomplished by skilled operators. Recently, the concept of automation is widely introduced in shipping and unloading operation using the overhead crane for the enhanced productivity. In this regards, we designed an angle detector and 3D position detectro which are key evices for this operation. As well as an intellignet control algorithm is developed for the implementation of swing free crane. The performance of the presented algorithm is tested for the swing angle and the position of the overheas crand. The control scheme adopts a feedback control of an angular velocity of swing in initial phase and then the fuzzy controller whose rule base is optimized by a genetic algorithm.

• Journal of Korean Association for Spatial Structures
• /
• v.16 no.3
• /
• pp.79-88
• /
• 2016

An outrigger damper system has been proposed to reduce dynamic responses of tall buildings. In previous studies, an outrigger damper system was optimally designed to decrease a wind-induced or earthquake-induced dynamic response. When an outrigger damper system is optimally designed for wind excitation, its control performance for seismic excitation deteriorates. Therefore, a smart outrigger damper system is proposed in this study to make a control system that can simultaneously reduce both wind and seismic responses. A smart outrigger system is made up of MR (Magnetorheological) dampers. A fuzzy logic control algorithm (FLC) was used to generate command voltages sent for smart outrigger damper system and the FLC was optimized by genetic algorithm. This study shows that the smart outrigger system can provide good control performance for reduction of both wind and earthquake responses compared to the general outrigger system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2003.09a
• /
• pp.517-520
• /
• 2003

A quasi-optimization algorithm for generating a chain restaurant work scheduling (WS) is proposed based on Genetic Algorithm with fuzzy logic, where the whole weekly chain restaurant WS problem is decomposed to 7 daily WS problems and a combined weekly WS problem. Experimental result shows that a weekly schedule for 15 workers and 24 hours in a chain restaurant is produced in 6 minutes using the proposed algorithm implemented with C++ and executed on a PC(Athlon XP 1900+), where the quality of WS is satisfactorily evaluated by professional experts.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.48 no.6
• /
• pp.704-711
• /
• 1999

This paper presents a design of fuzzy power system stabilizer (FPSS) using adaptive evolutionary computation (AEC). We have proposed an adaptive evolutionary algorithm which uses a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations. FPSS shows better control performances than conventional power system stabilizer (CPSS) in three-phase fault with heavy load which is used when tuning FPSS. To show the robustness of the proposed FPSS, it is appliedto damp the low frequency oscillations caused by disturbances such as three-phase fault with normal and light load, the angle deviation of generator with normal and light load and the angle deviation of generator with heavy load. Proposed FPSS shows better robustness than CPSS.