• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.1
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• pp.165-177
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• 2000

A fuzzy controller need membership functions and the control rules depend on heuristic knowledge of expertises entirely. On account of, it is possible that a desired performance of a fuzzy controller can not be guaranteed or easily degraded under some circumstances such as a change of plant parameter which exporters do not considered. Therefore, in this paper we tried to increase the controller's efficiency by adjusting the control rules and the parameters of the membership functions by using a genetic algorithm. We also proposed the Self-Organizing Fuzzy Controller which uses the Fusion Method in order to minimize the number of control rules and to construct the intuitive controller. For validation of the proposed algorithm, we design the Autonomous Guided Vehicle Controller, then apply to variant condition.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.102-107
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• 2000

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 tile 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2567-2576
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• 1994

In this paper we propose a new method to determine the learning rates of fuzzy learning algorithm(FLA) in nonlinear MIMO system. The state feedback gains are used from the linearized system of the nonlinear MIMO system. Through this method, it is easy to determine the learing rates. And it is quarauteed the good convergence and confirmed the performance of FLA is better than that of linear controller(LC) through the simulation. Acrobatic robot system is selected as an example(one-input two-output system), and FLA is implemented through the experiment.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.682-684
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• 1995

The most effective way to improve the performance of a fuzzy controller may be to optimize look-up values. Look-up values are derived from processes used input-output scale factors, membership functions, rule base, fuzzy inference method and defuzzification. It is powerful way to modify or organize look-up table values. In this paper, We propose the look-up values self-organizing fuzzy controller(LSOFC). We use the plus-minus tuning method(PMTM), scanning values through the processes of addition and subtraction. We show the efficiency of this LSOFC by the results of simulation for nonlinear time-varying plant with unmodelled dynamics.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.663-670
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• 1998

Most of feedback shift controllers developed in the past have fixed control parameters tuned by experts using a trial and error method. Therefore, those controllers cannot satisfy the best control performance under various driving conditions. To improve the shift quality under various driving conditions, a new self-organizing controller(SOC) that has an optimal control performance through self-learning of driving conditions and driver's pattern is designed in this study. The proposed SOC algorithm for the shift controller uses simple descent method and has less calculation time than complex fuzzy relation, thus makes real-time control passible. PCSV (Pressure Control Solenoid Valve) control current is used as a control input, and turbine speed of the torque converter is used indirectly to monitor the transient torque as a feedback signal, which is more convenient to use and economic than the torque signal measured directoly by a torque sensor. The results of computer simulations show that an apparent reduction of shift-transient torque is obtained through the process of each run without initial fuzzy rules and a good control performance in the shift-transient torque is also obtained.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.46-50
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• 1997

In fuzzy logic control, static fuzzy rules cannot cope with significant changes of parameters of plants or environment. To solve this prohlem, self-organizing fuzzy control. neural-network-hased fuzzy logic control and so on have heen introduced so far. However, dynamically changed fuzzy rules of these schemes may make a fuzzy logic controller Fall into dangerous situations because the changed fuzzy rules may he incomplete or inconsistent. This paper proposes a new adaptive filzzy logic control scheme using a predictivc neural network. Although some parameters of a controlled plant or environment are changed, proposed fuzzy logic controller changes its decision outputs adaptively and robustly using unchanged initial fuzzy rules and the predictive errors generated hy the predictive neural network by on-line learning. Experimental results with a D<' servo-motor position control problem show that propnsed cnntrol scheme is very useful in the viewpoint of adaptability.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.241-249
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• 2002

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 login 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. The proposed SOFC scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for robot with tow joints.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.69-72
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• 2003

사람은 이성과 감정을 가지고 있어, 동일한 환경 조건하에서도 감정에 따라 조금은 다른 행동을 보인다. 그러므로 아무리 정교한 행동을 할 수 있는 에이전트를 만든다 하더라고 로봇이 자체의 내부 감정을 동반하지 않으면, 능동적으로 상호 작용을 할 수 있는 에이전트를 구성할 수 없다 볼 수 있다. 본 논문에서는 감독학습, SOM(self-organizing Map) 그리고 fuzzy controller를 통해서, 주어진 환경에서 학습된 행동을 함에 있어서 감정의 변화를 고려해, 감정의 요소가 행동에 영향을 미치는 에이전트를 모델링하고자 한다. 또한 감정을 가진 모델을 통해 최종적으로 사람과 상호행동하는 모델에 대한 가능성을 제시하고자 한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.31-34
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• 1998

본 논문에서는 하이브리드 구조를 가지는 자기구성 퍼지제어기를 제안한다. 제안한 방법은 FARMA 제어기에 비해 다음과 같은 장점을 가진다. 하이브리드 구조를 자기구성 퍼지논리 제어기에 도입하므로써 예측출력값을 구할 때 까지의 입축력정보의 부재로 인한 나쁜 응답성능을 개선할 수 있다. 또한 이 방법은 Yager의 t-norm을 이용하여 계산상의 복잡성을 피하고 규칙들의 가중치를 구하기 위해 필요한 Dmax선정의 어려움을 해결한다.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.103.1-103
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• 2002

In variable structure control algorithms, The control law used to realized the desired sliding mode dynamics is discontinuous on the switching manifold. However, due to imperfections in switching, such as time delays, the system trajectory chatters instead of sliding along the switching manifold. This chattering is undesirable because it may excite unmodeled high frequency dynamics in the physical system. In this paper, to overcome this drawback a self-organizing fuzzy sliding mode control algorithm using gradient descent method is proposed. The proposed method has the characteristics which are viewed in conventional VSC, e.g. insensitivity to a class of disturbance, parameter variations and uncertainties ill the sliding mode. To demonstrate its performance, the proposed control algorithm is applied to an inverted pendulum system. The results show that both alleviation of chattering and performance are achieved.