• Journal of Mechanical Science and Technology
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• v.14 no.11
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• pp.1206-1215
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• 2000

This paper introduces the application of evolutionary fuzzy modeling (EFM) in constructing global function approximations to subsequent use in non-gradient based optimizations strategies. The fuzzy logic is employed for express the relationship between input training pattern in form of linguistic fuzzy rules. EFM is used to determine the optimal values of membership function parameters by adapting fuzzy rules available. In the study, genetic algorithms (GA's) treat a set of membership function parameters as design variables and evolve them until the mean square error between defuzzified outputs and actual target values are minimized. We also discuss the enhanced accuracy of function approximations, comparing with traditional response surface methods by using polynomial interpolation and back propagation neural networks in its ability to handle the typical benchmark problems.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.960-963
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• 1996

In this paper, the optimization of a fuzzy controller using genetic algorithm is studied. The fuzzy controller has been widely applied to industries because it is highly flexible, robust easy to implement and suitable for complex systems. Generally, the design of fuzzy controller has difficulties in determining the structure of the rules and the membership functions. To solve these problems, the proposed method optimizes the structure of fuzzy rules and the parameters of membership functions simultaneously in an off-line method. The proposed method is evaluated through computer simulations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.164-167
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• 2004

In the paper is proposed a hierarchical adaptive fuzzy controller for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the hierarchical adaptive fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing, a forced disturbance generator which emulates heuristic control strategy, and a supervisory decision maker for the arbitration of two control objectives It is proved that all the signals in the overall system are bounded. Simulation results are given to verify the proposed adapt i ye fuzzy control method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.178-183
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• 2004

This paper presents a class of hierarchical fuzzy systems where previous layer outputs are used not in IF-parts, but only in THEN -parts of the fuzzy rules of the current layer. The existence of the proposed hierarchical fuzzy system which approximates a given real continuous function on a compact set is proven if complete fuzzy sets are used in the IF-parts of the fuzzy rules with singleton fuzzifier and center average defuzzifier.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.238-242
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• 1991

This paper presents an approach to self-tuning PI control of dynamic plants, based on fuzzy logic application. 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 fuzzy logic controller, one of the most difficult problem is the selection of linguistic control rules and parameters. To overcome this difficulty, self-tuning fuzzy PI controller (STFPIC) with a hierarchical structure in which the fuzzy PI controller is assigned as the lower level and the rule modification and parameter adjustment as the higher level. The rules and parameters are generated by the adjustment of membership function through performance index(PE). In this paper, the algorithm for of the controller performance is estimated by means of computer simulation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.202-207
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• 2001

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller 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 variable of the controller, In the synthesis of a FLC, 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 level and high level that modify control rules.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.206-209
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• 1999

Conventional target tracking techniques are primarily based on Kalman filtering or probabilistic data association(PDA). But it is difficult to perform well under a high cluttered tracking environment because of the difficulty of measurement, the problem of mathematical simplification and the difficulty of combined target detection for tracking association problem. This paper deals with an analysis of target tracking problem using fuzzy-logic theory, and determines fuzzy rules used by a fuzzy tracker, and designs the fuzzy tracker by using fuzzy rules and Kalman filtering.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.285-294
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• 2000

This paper shows that the proposed fuzzy-sliding mode control algorithm for a SCARA robot could reduce the chattering due to sliding mode control and is robust against a change of payload and parameter uncertainties. That is, the chattering can be reduced by changing control input for compensating disturbances into a control input by fuzzy rules within a pre-determined dead zone. The experimental results show that the chattering can be reduced more effectively by the fuzzy-sliding mode control algorithm than the sliding mode control with two dead zones. It is proved experimentally that the proposed control algorithm is robust to a change of payload. The proposed control algorithm is implemented to the SCARA robot using a DSP(board) for high speed calculations.

• Journal of Mechanical Science and Technology
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• v.15 no.3
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• pp.339-350
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• 2001

To overcome problems in tracking error related to the unmodeled dynamics in the high speed operation of industrial robots, many researchers have used sliding mode control, which is robust against parameter variations and payload changes. However, these algorithms cannot reduce the inherent chattering which is caused by excessive switching inputs around the sliding surface. This study proposes a fuzzy-sliding mode control algorithm to reduce the chattering of the sliding mode control by fuzzy rules within a pre-determined dead zone. Trajectory tracking simulations and experiments show that chattering can be reduced prominently by the fuzzy-sliding mode control algorithm compared to a sliding mode control with two dead zones, and the proposed control algorithm is robust to changes in payload. The proposed control algorithm is implemented to the SCARA (selected compliance articulated robot assembly) robot using a DSP (digital signal processor) for high speed calculations.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.125-130
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• 1999

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller 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 variable of the controller, In the synthesis of a FLC, 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 level and high level that modify control rules.