• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1102-1105
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• 1993

A fuzzy expert system for prediction and mitigation of sludge bulking was developed for an activated sludge process which treats waste water from a food industry. The developed system is able not only to infer the degree of progress of sludge bulking but also to generate remedial operation guides which may be sent to the local controllers as remote set points. One of the important consequences through this study is the BI (Bulking Index) inferred by the bulking prediction expert system was found to have a close correlation with the SVI (Sludge Volume Index) which is a practical measure of degree of bulking but needs tedious chores for its measurement.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.818-821
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• 1993

In the last years fuzzy control has grown up to an important methodology of control engineering. In spite of the successful realizations of the underlying concepts in industrial products there has only been little effort regarding a semantical foundation of the prevailing heuristics that are used in fuzzy control. For this reason we want to outline promising approaches to an interpretation and better mathematical justification of fuzzy control, where the fundamental ideas of using equality relations to specify fuzzy environments for crisp data are presented. It turns out that Mamdani's classical max-min-inference is a consequence of our model.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.822-825
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• 1993

A fuzzy logic controller derived from the variable structure control (VSC) theory is designed. Unlike the conventional design of the fuzzy controller, we do not fuzzify the error and the rate of error, but fuzzify the sliding surface. After the fuzzy sliding surface is introduced, the fuzzy rules are defined based on the sliding control theory. It will be shown this sliding mode fuzzy controller is a kind of VSC that introduces the boundary layer in the switching surface and that the control input is continuously approximated in the layer. As a result we can guarantee the stability and the robustness by the help of VSC, which were difficult to insure in the past fuzzy controllers. Simulation results for the inverted pendulum will show the validity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.826-829
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• 1993

Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unknown deadzones. We propose a novel two-layered fuzzy logic controller for controlling systems with deadzones. The two-layered control structure consists of a fuzzy logic-based pre-compensator followed by a conventional fuzzy logic controller. Our proposed controller exhibits superior transient and steady-state performance compared to conventional fuzzy controllers. We illustrate the effectiveness of our scheme using computer simulation examples.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1029-1032
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• 1993

The construction of the rulebase of a fuzzy controller is usually difficult because experts' knowledge is often hard to derive. To remedy such a problem, a number of self-learning schemes for rulebase formulations were proposed. One of the popular approaches is the reinforcement learning. Many successful examples employing such an idea were proposed and claimed to be with good results in the literature. The purpose of this paper is to discuss and make comparisons between some of the related work in order to provide a better picture regarding their performances. A numerical algorithm for the analysis of nonlinear as well as fuzzy dynamic systems, the Cell-to-Cell Mapping, is used. The analytical results reveals the true behavior of the learning schemes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.113-117
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• 2002

PID controllers, which have been widely used in industry, have a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose a nonlinear adaptive PR controller based on an Immune feedback mechanism and a gradient descent teaming. This algorithm has a simple structure and robustness to system parameters variation. To verify performances of the proposed nonlinear adaptive PID controller, the speed control of nonlinear DC motor Is peformed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1196-1201
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• 2014

This paper presents an exploration on the effect of wind turbine contribution to the frequency control of individual systems that can be used for efficient power production in India. The research includes the study of Permanent Magnet Synchronous Generator (PMSG), in wind farms. The WTs are tested for inertia and for droop responses with intelligent fuzzy logic controllers (FLC) that choose Double Input Single Output (DISO) strategy that automatically sets gain constants, as well as combined responses for the WTs. Quantitative analyses are presented for the WTs for benefits and drawbacks including appropriate selection parameters. The analysis includes inertia, droop and combined inertia, droop schemes. The reconnaissance also incorporates inertia with FLC, droop with FLC, inertia and droop with FLC schemes for detailed study of WTs, so as to forecast and achieve proper frequency control. Moreover, the analysis provides the best suited method for frequency control in PMSG.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.514-517
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• 2005

Microstereolithography(MSL) has evolved from the stereolithography technique, and is also based on a light-induced layer-stacking fabrication. Although integral MSL allows the manufacture of a complete layer by one irradiation only, there is a problem related with shape precision due to the light-intensity distribution of focused image. In this study, we developed the integral MSL apparatus using Digital Micromirror Device ($DMD^{TM})$, Texas Instruments) as dynamic pattern generator. It is composed of Xenon-Mecury lamp, optical devices, pattern generator, precision stage, controllers and the control program. Also, we have studied curing depth and width of photocurable resin according to the change of exposure energy.

• Journal of Drive and Control
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• v.17 no.4
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• pp.8-14
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• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.765-768
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• 1993

Adaptive Control is used in order to improve close loop dynamics with a fuzzy controller when process parameters are unknown or fluctuate form an initial value. The way in which the adaptive control environment may be applied is the following. First we obtain a linear fuzzy controller. Second, we apply the adaptive rules by means of actuating directly over fuzzy variables which change their value. The techniques are based on Lyapunov functions. Third, we comment about extending this method to non-piecewise linear controllers using the contrast definition for a fuzzy controller.