• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.249-255
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• 2000

HRIV(Hybrid Rule-Interval Variation) method is presented to stabilize a class of nonlinear systems, where SMC(Sliding Mode Control) and ADC (ADaptive Control) schemes are incorporated to overcome the unstable characteristics of a conventional FLC(Fuzzy Logic Control). HRIV method consists of two modes: I-mode (Integral Sliding Mode PLC) and R-mode(RIV method). In I-mode, SMC is used to compensate for MAE(Minimum Approximation Error) caused by the heuristic characteristics of FLC. In R-mode, RIV method reduces interval lengths of rules as states converge to an equilibrium point, which makes the defined Lyapunov function candidate negative semi-definite without considering MAE, and the new uncertain parameters generated in R-mode are compensated by SMC. In RIV method, the overcontraction problem that the states are out of a rule-table can happen by the excessive reduction of rule intervals, which is solved with a dynamic modification of rule-intervals and a transition to I-mode. Especially, HRIV method has advantages to use the analytic upper bound of MAE and to reduce Its effect in the control input, compared with the previous researches. Finally, the proposed method is applied to stabilize a simple nonlinear system and a modified inverted pendulum system in simulation experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.322-327
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• 2003

The water level of a steam generator of pressurized light water nuclear Power generator is known as a subject whose control is difficult because of a shrinking and swelling effect that is been mutually contradictory in a variation of feed water. In this paper, a neural network model selects first coordinative controller by a inappropriate gain of two PI controllers and the selected controller＇s gain is tuned by a fuzzy self-tuner. Model inputs consist of the water level, the feed water, and the stream flow. One controller of both coupling controllers whose gain is handled firstly is decided based upon above data. The proposed method can analyze patterns of signals using the characteristic of neural networks and select one controller that needs to be tuned through the observed result in this paper. If one controller between both the water level controller and the feed water controller is selected by the neural network model then a gain of the PI controller is suitably tuned by the fuzzy self-tuner. Rules of the fuzzy self-tuner drew from the pattern of input and output data. In the summary, the goal of this Paper is to select the suitable controller and tune the control gain of the selected controller suitably through such two processes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.591-595
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• 1998

This paper proposes a new concept of optimal shortest path algorithm which reduce average vehicle wating time and improve average vehicle speed, Electro sensitive traffic system can extend the traffic cycle when three are many vehicles on the road or it can reduce the traffic cycle when there are small vehicles on the road. But electro sensitive traffic light system doesn't control that kind of function when the average vehicle speed is 10km -20km. Therefore, in this paper to reduce vehicle waiting time we developed design of traffic cycle software tool that can arrive destinination as soon as possible using optimal shortest pass algorithm. Computer simulation result proved 10%-32% reducing average vehicle wating time and average vehicle speed which can select shortest route using built in G.P.S. vehicle is better than not being able to select shortest route function.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.446-451
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• 1992

In this paper, we propose a method to manage production system easily for operators when either equipments or products are changed. And we explain the scheduling AI tool which realizes the proposal method. The tool's knowledge expression consists of models, rules, mathematical expression and fuzzy logic. The model expresses the relations between products and manufacture, and properties of products. The models are separated into three type, equipment model, operation model, and product model. These models are classified by applicable fields as the assembly process or continuous plant process, The model expression of each type is based on object oriented paradigm. We report systems utilizing our approach.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.225-230
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• 2023

This research addresses sound command based human tracking problems for autonomous cleaning mobile robot in a networked AI space. To solve the problem, the difference among the traveling times of the sound command to each of three microphones has been used to calculate the distance and orientation of the sound from the cleaning mobile robot, which carries the microphone array. The cross-correlation between two signals has been applied for detecting the time difference between two signals, which provides reliable and precise value of the time difference compared to the conventional methods. To generate the tracking direction to the sound command, fuzzy rules are applied and the results are used to control the cleaning mobile robot in a real-time. Finally the experiment results show that the proposed algorithm works well, even though the mobile robot knows little about the environment.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.62-66
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• 2017

In this paper, we present the development of communication and data processing strategy for the electromagnetic wave precipitation gauge system. The electromagnetic wave precipitation gauge system is a small system for deriving area rainfall rates within 1 km radius through dual polarization radar observation at 24GHz band. It is necessary to take consider for measurement of accurate precipitation under limited computing resources originating from small systems and to minimize the use of network for the unattended operation and remote management. To overcome computational resource limitations, we adopted the fuzzy logic for quality control to eliminate non-precipitation echoes and developed the method by weighted synthesis of various rain rate fields using multiple radar QPE formulas. Also we have designed variable data packets rules to minimize the network traffic.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.2
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• pp.18-35
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• 1993

The water level control system of the steam generator in a pressurized water reactor and its control problems are analysed. In this work the stable control strategy during the low power operation and transient states is studied. To solve the problem, a fuzzy logic control method is applied as a basic algorithm of the controller. The control algorithm is based on the operator's knowledges and the experiences of manual operation for water level control at the compact nuclear simulator set up in Korea Atomic Energy Research Institute. From a viewpoint of the system realization, the control variables and rules are established considering simpler tuning and the input-output relation. The control strategy includes the dynamic tuning method and employs a substitutional information using the bypass valve opening instead of incorrectly measured signal at the low flow rate as the fuzzy variable of the flow rate during the pressure control mode of the steam generator. It also involves the switching algorithm between the control valves to suppress the perturbation of water level. The simulation results show that both of the fine control action at the small level error and the quick response at the large level error can be obtained and that the performance of the controller is improved.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.821-832
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• 1998

This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.9 s.351
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• pp.135-141
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• 2006

In order to prevent traffic accident, it is very important that the driver regulates the location of rear view mirror using the automatic seat regulation system which guarantees the maximum vision of the possibility for accuracy. In order to solve this problem the paper deals with the automatic seat control system which guarantees comfortable and safe seating and good visual field. Also a automatic car seat control algorithm has been developed to regulate the back mirror. Particularly, the automatic seat control algorithm function for the air bag operation in case of an accident has been added depending on passengers weight. Moreover when the driver passes a dangerous area an algorithm has been developed which gives the driver a naming sign and has been simulated in a ubiquitous environment. The simulation result proved that the Intelligence analysis for traffic accidents can reduce franc accidents more than 25% than the currently existing methods.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.2
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• pp.188-198
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• 2013

In constructing a collision avoidance system, it is important to determine the time for starting collision avoidance maneuver. Many researchers have attempted to formulate various indices by applying a range of techniques. Among these indices, collision risk obtained by combining Distance to the Closest Point of Approach (DCPA) and Time to the Closest Point of Approach (TCPA) information with fuzzy theory is mostly used. However, the collision risk has a limit, in that membership functions of DCPA and TCPA are empirically determined. In addition, the collision risk is not able to consider several critical collision conditions where the target ship fails to take appropriate actions. It is therefore necessary to design a new concept based on logical approaches. In this paper, a collision ratio is proposed, which is the expected ratio of unavoidable paths to total paths under suitably characterized operation conditions. Total paths are determined by considering categories such as action space and methodology of avoidance. The International Regulations for Preventing Collisions at Sea (1972) and collision avoidance rules (2001) are considered to solve the slower ship's dilemma. Different methods which are based on a constant speed model and simulated speed model are used to calculate the relative positions between own ship and target ship. In the simulated speed model, fuzzy control is applied to determination of command rudder angle. At various encounter situations, the time histories of the collision ratio based on the simulated speed model are compared with those based on the constant speed model.