• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2261-2263
• /
• 2001

Fuzzy controller design consists of intuition, and any other information about how to control system, into a set of rules. These rules can then be applied to the system. It is very important to decide parameters of IF-THEN rules. Because fuzzy controller can make more adequate force to the plant by means of parameter optimization, which is accomplished by learning procedure. In this paper, we apply fuzzy controller designed to the Swing-UP Inverted pendulum.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.161.4-161
• /
• 2001

This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.182-182
• /
• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.11
• /
• pp.80-92
• /
• 1997

This research focuses onan efficient control method of temperature for multiple points using only one processor. For a yarn production system, the surface temperature control of heaters are very important for quality control. Therefore, we designed a temperature controller for a draw and twist machine and applied Fuzzy-PWM algorithm to the controller. If we use a processor for the temperature control of multiple points with the conventional ON/OFF control, the control performance of the system becomes poor. To overcome these problems, we developed a new Fuzzy-PWM algorithm for the adjustment of power rate to the heaters in the conventional ON/OFF control. It is shown that this algorithm has the same effects as the PID algorithm for the temperature control of each point. The proposed algorithm is robust against the production condition and environment such as the reference temperature and the thickness of yarn, since the power rate to the heater is adjusted by Fuzzy Rules derived from the values of the reference termperatureand the thickness of yarn. To obtain optimal Fuzzy rulees, the control simulations are perfodrmed through the modelling of the heater and simulation of Fuzzy rules. This algorithm is applied for the multiple pont temperature controller and showed satisfactory performance.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.13 no.1
• /
• pp.35-47
• /
• 2004

In this paper presents a new approach to the design and real-time implementation of fuzzy control system based-on digital signal processors(DSP:IMS320C80) in order to improve the precision and robustness for system of industrial robot(Dual-Arm with 8 joint Robot). The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The IMS320C80 is used in implementing real time fuzzy control to provide an enhanced motion control for robot manipulators. In this paper, a Self-Organizing Fuzzy Controller(SOFC) for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variables of the controller. In the synthesis of a FLC(Fuzzy Logic Controller), one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult SOFC is proposed for a hierarchical control structure consisting of basic and high levels that modify control rules. The proposed SOFC scheme is simple in structure, Int in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for a Dual-Arm robot with eight joints.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.2
• /
• pp.187-196
• /
• 2006

A new GA-based methodology using information granules is suggested for the construction of fuzzy classifiers. The proposed scheme consists of three steps: selection of information granules, construction of the associated fuzzy sets, and tuning of the fuzzy rules. First, the genetic algorithm (GA) is applied to the development of the adequate information granules. The fuzzy sets are then constructed from the analysis of the developed information granules. An interpretable fuzzy classifier is designed by using the constructed fuzzy sets. Finally, the GA is utilized for tuning of the fuzzy rules, which can enhance the classification performance on the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example, the classification of the Iris data, is provided.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.676-680
• /
• 1991

This paper proposes fuzzy control algorithms for a DC moter speed control. The proposed algorithms are constructed by the fuzzy controller and the fuzzy compensator. The fuzzy compensator used to overcome rapidly the effects caused by the disturbance and is mounted outside of the closed loop of the fuzzy controller. The fuzzy control rules are established from human operator experience and basic engineering knowledge about the process dynamics. Simulation results show that the proposed algorithms compensate for parameter variation and disturbance.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.689-693
• /
• 1996

• Journal of the Korean Society for Precision Engineering
• /
• v.21 no.3
• /
• pp.30-37
• /
• 2004

This thesis develops a fuzzy-PID control algorithm for control the filament winding tension. It is developed by applying classical PID control technique to a fuzzy logic controller. It is composed of a fuzzy-PI controller and a fuzzy-D controller. The fuzzy-PI controller uses error and integrated error as inputs, and the fuzzy-D controller uses derivative of error as input. The fuzzy-PI controller uses Takagi-Sugeno fuzzy inference system, and the fuzzy-D controller uses Mamdani fuzzy inference system. The fuzzy rule base for the fuzzy-PI controller is designed using 19 rules, and the fuzzy rule base for the fuzzy-D controller is designed using 5 rules. A test-bed is set-up for verifying the effectiveness of the developing control algorithm in control the filament winding tension. It is composed of a mandrel, a carriage, a force sensor, a driving roller, nip rollers, a creel, and a real-time control system. Nip rollers apply a vertical force to a filament, and the driving roller drives it. The real-time control system is developed by using MATLAB/xPC Target. First, experiments for showing the inherent problems of an open-loop control scheme in a filament winding are performed. Then, experiments for showing the robustness of the developing fuzzy-PID control algorithm are performed under various working conditions occurring in a filament winding such as mandrel rotating speed change, carriage traversing, spool radius change, and reference input change.

• Proceedings of the IEEK Conference
• /
• 2003.07c
• /
• pp.2863-2866
• /
• 2003

In nonlinear control fields, for irregular nonlinear systems, control form which consists of approximate tracking control law and exact tracking control law and which switches between two laws has been proposed recently. In this thesis, we design new switching control law which connect approximate linearization control law and exact linearization control law by fuzzy rules for irregular nonlinear system, ball and beam system. Fuzzy switching controller designed by fuzzy concept is proved that designed scheme overcomes singularities of irregular system, improves unstability problem of switching procedure, and has more efficient control value through simulation. Stability of fuzzy control system proved by Lyapunov's stability theorems.