• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.50 no.12
• /
• pp.561-567
• /
• 2001

This paper describes the application of Fuzzy Logic Controller (FLC) to Thyristor Controlled Series Capacitor (TCSC) which can have significant impact on power system dynamics. The function of the FLC is to control the firing angle of the TCSC. We tuned the scaling factors of the FLC using Tabu Search. The proposed FLC is used for damping the low frequency oscillations caused by disturbances such as the sudden changes of small or large loads or the outages in the generators or transmission lines. To evaluate usefulness of the proposed FLC, we performed the computer simulation fur single-machine infinite system. The response of FLC is compared with that of PD controller optimized using Tabu Search. Simulation results that the FLC shows better control performance than PD controller.

• Geomechanics and Engineering
• /
• v.31 no.3
• /
• pp.291-304
• /
• 2022

Maximum shear modulus (G_max or G₀) is an important soil property useful for many engineering applications, such as the analysis of soil-structure interactions, soil stability, liquefaction evaluation, ground deformation and performance of seismic design. In the current study, bender element (BE) tests are used to evaluate the effect of the void ratio, effective confining pressure, grading characteristics (D₅₀, C_u and C_c), anisotropic consolidation and initial fabric anisotropy produced during specimen preparation on the G_max of sand-gravel mixtures. Based on the tests results, an empirical equation is proposed to predict G_max in granular soils, evaluated by the experimental data. The artificial neural network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) models were also applied. Coefficient of determination (R²) and Root Mean Square Error (RMSE) between predicted and measured values of G_max were calculated for the empirical equation, ANN and ANFIS. The results indicate that all methods accuracy is high; however, ANFIS achieves the highest accuracy amongst the presented methods.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.4 no.4
• /
• pp.180-189
• /
• 2009

Currently, most automobile companies are interested in research on intelligent autonomous vehicle. They are mainly focused on driver's intelligent assistant and driver replacement. In order to develop an autonomous vehicle, lateral and longitudinal control is necessary. This paper presents a lateral and longitudinal control system for autonomous vehicle that has only mono-vision camera. For lane detection, we present a new lane detection algorithm using clothoid parabolic road model. The proposed algorithm in compared with three other methods such as virtual line method, gradient method and hough transform method, in terms of lane detection ratio. For adaptive control, we apply a vanishing point estimation to fuzzy control. In order to improve handling and stability of the vehicle, the modeling errors between steering angle and predicted vanishing point are controlled to be minimized. So, we established a fuzzy rule of membership functions of inputs (vanishing point and differential vanishing point) and output (steering angle). For simulation, we developed 1/8 size robot (equipped with mono-vision system) of the actual vehicle and tested it in the athletics track of 400 meter. Through the test, we prove that our proposed method outperforms 98 % in terms of detection rate in normal condition. Compared with virtual line method, gradient method and hough transform method, our method also has good performance in the case of clear, fog and rain weather.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.1
• /
• pp.88-93
• /
• 2010

In this paper, an edge detecting sensor using ultrasonic detection module is developed which will be used for areas of industrial applications such as plastic film winding system, cloth winding system, paper roll industry, etc. The developed sensor have properties that more exactly detect the edge line, that less affected by environmental noise, and that it produced more stable measurement output. The mass of the winding object is dominantly affect the dynamics of the system and it could produce undesirable result of the system such as stability of the closed-loop system and accuracy of edge-line-following-control(ELFC) objective. Also, there exist sensor noise due to the mechanical vibration or other environmental effect. These noise also degrade the efficiency of control system. In order to compensate these problems, this paper present a fuzzy PI/PID edge-line-controller, and which is designed and implemented.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.6
• /
• pp.1379-1386
• /
• 2005

For efficient welding it is necessary to maintain stability of the welding process and control the shape of the welding bead. The welding quality can be controlled by monitoring important parameters, such as, the Arc Voltage, Welding Current and Welding Speed during the welding process. Welding systems use either a vision sensor or an Arc sensor, both of which are unable to control these parameters directly. Therefore, it is difficult to obtain necessary bead geometry without automatically controlling the welding parameters through the sensors. In this paper we propose a novel approach using fuzzy logic and neural networks for improving welding qualify and maintaining the desired weld bead shape. Through experiments we demonstrate that the proposed system can be used for real welding processes. The results demonstrate that the system can efficiently estimate the weld bead shape and remove the welding detects.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.6 no.2
• /
• pp.3-12
• /
• 1996

Sliding mode controller(SMC) is a simple but powerful nonlinear controller, because it guarantees the stability and the robustness. However, it leads to the high frequency chattering of the control input. Although the phenomenon can be avoided by introducing a thin boundary layer to the sliding surface, the method results in a steady state: error proportional to the boundary layer thickness. In this paper, we proposed a new sliding mode controller with self-tuning the thickness of a boundary layer. It uses a fuzzy rule base for tuning the thickness of a boundary layer. That is, the thickness is increased to some degree to reject a discontinuous control input at the initial state and then it is decreased as the states approaches to the steady states for improving the tracking performance. In order to assure the control performance, we perf'ormed the computer simulation using an inverted pendulum system as a controlled plant.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.2
• /
• pp.144-150
• /
• 2013

The purpose of this study was to evaluate the competence level of the caregiver and verify empirically the evaluated score of the competence level of the caregiver depending on the type of career and employment to propose a measure to improve the quality of care services. To more accurately evaluate the competence level of caregiver, the collected data were analyzed using fuzzy relationships for identifying the extent of relationship, after setting weighted values for the evaluation factors for working levels and service qualities. Such approach has a significance in that individual evaluation factors and individual's competence levels for caregivers may be more suitably and exactly identified. The analysis results are as follows. Care skill, reliability, assurance, typicality were statistically significant according to the caregiver's career. Also, according to the types of employment, job consciousness, responsiveness, empathy, typicality were statistically significant. To improve the competence level of the caregiver, it may be seen that improvement of job consciousness considering the career and employment types and making environments for acquiring the care skills should be done, while providing stability of the employment types rather than careers is more meaningful to improve the quality of services.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.2
• /
• pp.138-143
• /
• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.2
• /
• pp.168-173
• /
• 2015

The flight control of aircraft, which has nonlinear time-varying dynamic characteristics depending on the various and unexpected external conditions, can be performed on two motions: longitudinal motion and lateral motion. In the longitudinal motion control of aircraft, pitch and trust are major control parameters and roll and yaw are control ones in the lateral motion control. Until now, a number of efficient and reliable control schemes that can guarantee the stability and maneuverability of the aircraft have been developed. Recently, the intelligent flight control scheme, which differs from the conventional control strategy requiring the various and complicate procedures such as the wind tunnel and environmental experiments, has attracted attention. In this paper, an intelligent longitudinal control scheme has been proposed utilizing Interval Type-2 fuzzy logic which can be recognized as a representative intelligent control methodology. The results will be verified through computer simulation with a F-4 jet fighter.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.12
• /
• pp.6034-6039
• /
• 2012

In this paper, this may appear to exacerbate it met slopes of the mobile robot moves to overcome this by driving can occur if the mobile robot system has its own sleep problems driving progress in until you hit the target and solvedriving straight driving safer model for adaptive fuzzy control method of mobile robot based control algorithm is proposed. First, we propose a model based adaptive fuzzy controller, if possible, the dynamics model of the mobile robot, including model-based controller is designed to determine if you can check the condition of the mobile robot climbing and driving the mobile robot to overcome the slope and the to overcome driving control. Enough considering the ground friction forces and ensure the stability of the mobile robot system and the disturbance compensation, etc. In this case, the controller design will be possible. In addition, the nonlinear model, the dynamic characteristics of the mobile robot control method of adaptive fuzzy control techniques in the design that you want to fully reflect Non-holonomic system of mobile robots and solve sleep problems, and will be useful enough, it was verified through computer simulations.