• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.411-419
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• 1998

In this paper the steady-state genetic algorithm is applied for the optimal design of fuzzy PID controllers. Basically the structure of the discussed fuzzy PID controller is extended from the conventional fuzzy PI and PD controllers where only a two-dimensional rule base of the fuzzy PID controller are designed simultaneously. Simulations results shows the superior performance of this optimal designed fuzzy PID controllers to the optimal designed conventional fuzzy PI and PD controllers.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.2
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• pp.35-40
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• 1994

Fuzzy logic controllers are often found to behave better than PI controllers. One of the major reasons for this is that the fuzzy logic inferences used can produce nonlinear type controllers. For some applicatioins, howeveer, linear fuzzy logic controllers also perofrm better than PI controllers. In this paper, we examine linear fuzzy logic controllers to show that the truncation effects of the fuzzy logic controllers make them perform much better than the PI controllers. In terms of a performance index we used, the truncation effects reduced the index value by up to 80% for examples we studied.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1509-1512
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• 1996

This paper presents an intelligent autopilot for STT missiles with multiple controllers. The mixed H$_{2}$/H$_{\infty}$ control technique is applied for each controller and implemented by using the genetic searching algorithm. To facilitate automatic switching of multiple controllers under different operating conditions, an error based switching scheme is also combined with the multiple controllers at the higher level, which constitutes a hierarchical intelligent control system. It is shown via computer simulation that the proposed autopilot outperforms the conventional one..

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1729-1734
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• 2005

The use of gantry crane systems for transporting payload is very common in industrial application. However, moving the payload using the crane is not an easy task especially when strict specifications on the swing angle and on the transfer time need to be satisfied. To overcome this problem, this paper describes development of an intelligent gantry crane system based on the mechatronic design. A lab-scale gantry crane is designed and then its intelligent controllers are developed. Fuzzy logic controllers are adopted, designed and implemented for controlling payload position as well as the swing angle of the gantry crane. The performance of the intelligent gantry crane system is evaluated on a hardware-in-the-loop simulation (HILS) environment. Moreover robustness of the proposed system is also evaluated. The result shows that the intelligent gantry crane system designed based on the mechatronic design approach has better performance compared with the automatic gantry crane system controlled by classical PID controllers. Moreover simulation result shows that the intelligent gantry crane system is more robust to parameter variation than the automatic gantry crane system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.154-160
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• 2009

A control system composed of two fuzzy controllers is proposed to balance the pole as well as to move the cart to the center of the track of the cartpole system. The two fuzzy controllers are designed with 2 input variables respectively and their control characters are studied in order to devise a control scheme that alternates the two fuzzy controllers. It is found that the control system using the scheme works well even though there is some residual oscillations of the pole and the cart.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.150-161
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• 1999

This paper deals with the design and development of a real-time integrated communication architecture for heterarchical SFCS(Shop Floor Control System). In autonomous agent-based heterarchical SFCS, each functional unit of parts and resources is equipped with an intelligent controller (agent) that acts as the representative of the entity. The controllers communicate and negotiate with other controllers on a real-time basis through message passing and bidding protocol to achieve mutual agreements for task sharing. ICPL(Integrated Communication Protocol and Language) is proposed for this purpose. ICPL is a language and a protocol for supporting communication among intelligent controllers. Based on the speech act theory, this paper proposes a semantic description for ICPL that associates the description of the cognitive states of controllers with the use of language primitives (message_type). Semantics for the basic set of ICPL messages is described. Eventually, an ICPL-based communication architecture can provide the implementation of the distributed and heterarchical SFCS, and makes the intelligent controller transparent to the negotiation problem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.334-337
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• 2003

The emission of dioxins from waste incinerators is one of the most important environmental problems today, It is known that optimization of waste incinerator controllers is a very difficult problem due to the complex nature of the dynamic environment within the incinerator. In this paper, we propose applying artificial neural networks to waste incinerator controllers. We show that artificial neural networks can project the emission of dioxins with a fair degree of accuracy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.22-29
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• 2007

Two fuzzy controllers defined by 2 input variables cooperate to control a cartpole system in terms of balancing as well as centering. The cooperation is due to the BOXES scheme that selects one of the fuzzy controllers for each time step according to the content of box that is established through the critic of the control action by the fuzzy controllers. It is found that the control scheme is good at controlling the cartpole system so that the system is stabilized fast while the BOXES develops its ability to select proper fuzzy controller through experience.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1062-1065
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• 1993

Nuclear reactor operation is a human intensive task; one of the features of a problem for which fuzzy controllers present the most suitable solution. The performance of the fuzzy controllers can further be improved through tuning. In this work, application of a fuzzy controller in real-time control of a nuclear reactor is presented. The fuzzy controller is tuned on-line using direct gradient search method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.267-273
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• 2007

This paper presents the implementation of an educational kit for intelligent system control education. Neural network control algorithms are presented and control hardware is embedded to control the inverted pendulum system. The RBF network and the MLP network are implemented and embedded on the DSP 2812 chip and other necessary functions are embedded on an FPGA chip. Experimental studies are conducted to compare performances of two neural control methods. The intelligent control educational kit(ICEK) is implemented with the inverted pendulum system whose movements of the cart is limited by space. Experimental results show that the neural controllers can manage to control both the angle and the position of the inverted pendulum systems within a limited distance. Performances of the RCT and the FEL control method are compared as well.