• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2552-2556
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• 2005

In general, the forklift driven by DC motor drive system is used in the industrial field. Classically, the DC motor is controlled by current control using proportion control method, by output torque following the load on the plane like a manual operation. But in the industrial field, the forklift is demanded the robust drive mode. Some cases of the mode, there aretrouble in torque control following slope capacity. The control is sensitive concerning about slope angle and output speed, various control method is studied for stability of speed control. In this paper, I apply current control for the self-tuning using the fuzzy controller to obtain robust, stable speed control and use stable, high efficiency control using DSP as main controller for high speed processor, embody dynamic characteristic of control compared the PI controller to the fuzzy controller.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.373-375
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• 2004

The SRM is more robust and lower cost than other type motors. The inverter for SRM cannot have shoot through fault, since a phase winding of SRM is independent of other phase windings. The SRM has high starting torque and high power density. But it has torque ripples due to nonlinear magnetic characteristics. Therefore, SRM has highly non-linear torque producing characteristics. Because fuzzy logic is a flexible and general-purposed method for implementing non-linear dynamic functions, it is effective for the control of high current SRM. We design the fuzzy controller and demonstrate the fuzzy control system by MATLAB.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2005.03a
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• pp.469-476
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• 2005

To date, many viable smart base isolation systems have been proposed. In this study, a novel friction pendulum system (FPS) and an MR damper are employed as the isolator and supplemental damping device, respectively. A fuzzy logic controller (FLC) is used to modulate the MR damper. A genetic algorithm (GA) is used for optimization of the FLC. The main purpose of employing a GA is to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. To this end, a GA with a local improvement mechanism is applied. Neuro-fuzzy models are used to represent dynamic behavior of the MR damper and FPS. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can find appropriate fuzzy rules and the GA-optimized FLC outperforms not only a passive control strategy but also a human-designed FLC and a conventional semi-active control algorithm.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2461-2463
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• 2000

This paper presents a scheme for designing a fuzzy observer for servo control system with nonlinear element, i.e., backlash. It is found that backlash occurs when the feed direction is reversed. Due to the imperfect transient response of the driving mechanism, not only the static backlash error but also the dynamic backlash error is generated on the contouring profile. And also, we utilized two inertia modeling in order to deals with coupled system accurately. The overall control system consists of two parts - a servo controller and an Fuzzy obsever. It is a Takagi-sugeno type fuzzy model whose consequent part is of the state space form is obtained. A simulation is carried out to demonstrate the effectiveness of the proposed scheme.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.40-44
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• 2002

In this paper, robust control method using fuzzy PI parameter tuning is proposed to control constant thrust force on load variation. First, a structure and thrust force equations of the LPM are described. Second, an controller with PI parameter-tuning using a fuzzy theory is proposed to achieve high-precision position with constant thrust force of the LPM. Finally, the effectiveness of an fuzzy PI controller is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line Fuzzy PI gain tuning method with regard parametric variations and load thrust force variations.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.2
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• pp.225-235
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• 2005

In this Paper, it was designed the GA-fuzzy controller of a Thyristor Controlled Series Capacitor(TCSC) for enhancement of power system stability. The newly designed controller of TCSC was designed to overcome the nonlinearity such as operating point change of power system as well as to respond to disturbances as uncertainties of line parameters and line fault. So, fuzzy controller by intelligent control theory was used for it. And the fuzzy controller was optimized from a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller namely. scaling factor. membership function and control rules. Nonlinear simulation results show that the proposed control technique is superior to conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.12
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• pp.89-99
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• 2008

In this paper, the position tracking control problem of the servo system with nonlinear dynamic friction is issued. The nonlinear dynamic friction contains a directly immeasurable friction state variable and the uncertainty caused by incomplete parameter modeling and its variations. In order to provide the efficient solution to these control problems, we propose the composite control scheme, which consists of the robust friction state observer, the FNN approximator and the approximation error estimator with sliding mode control. In first, the sliding mode controller and the robust friction state observer is designed to estimate the unknown internal state of the LuGre friction model. Next, the FNN estimator is adopted to approximate the unknown lumped friction uncertainty. Finally, the adaptive approximation error estimator is designed to compensate the approximation error of the FNN estimator. Some simulations and experiments on the servo system assembled with ball-screw and DC servo motor are presented. Results show the remarkable performance of the proposed control scheme. The robust friction state observer can successfully identify immeasurable friction state and the FNN estimator and adaptive approximation error estimator give the robustness to the proposed control scheme against the uncertainty of the friction parameters.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.73-82
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• 1995

The paper demonstrates that an adaptive fuzzy controller can be used effectively for the control of the temperature and density of the Tokarnak fusion recator which is nonlinear and has dynamic uncertainties. The dynamic uncertainties are non-parametric but state dependent. Thus the conventional adaptive nonlinear control methods have difficulties to cope with the problem. The proposed adaptive fuzzy controller can be used as a solution and performs well in a predetermined local space. Simulation result verifies the effectiveness of the scheme.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.123-126
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• 2000

An elevator system which is a essential equipment for a vertical movement of object, as a property of building, have been drove by various expenditure and purpose. Since developing electrical control technology, control systems are highly developed. An elevator equipment is expended to wide, but a data accuracy acquisition technique and safety predict technique for securing system safety is still basic level. So, objective verification for elevator confidence condition is required absolutely accuracy measurement technique. Therefore, this study is accomplished in order to conquer a method of depending on sense of a manager with a simple numeric measurement data, and construct a logical, analytical foresight system for more efficient elevator management system.

• Journal of information and communication convergence engineering
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• v.11 no.1
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• pp.24-29
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• 2013

In this paper, we propose a fuzzy inference model for a navigation algorithm for a mobile robot that intelligently searches goal location in unknown dynamic environments. Our model uses sensor fusion based on situational commands using an ultrasonic sensor. Instead of using the "physical sensor fusion" method, which generates the trajectory of a robot based upon the environment model and sensory data, a "command fusion" method is used to govern the robot motions. The navigation strategy is based on a combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance based on a hierarchical behavior-based control architecture. To identify the environments, a command fusion technique is introduced where the sensory data of the ultrasonic sensors and a vision sensor are fused into the identification process. The result of experiment has shown that highlights interesting aspects of the goal seeking, obstacle avoiding, decision making process that arise from navigation interaction.