• Journal of Information Processing Systems
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• v.18 no.6
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• pp.763-769
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• 2022

Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.131-136
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• 2012

If one can find a control Lyapunov function (CLF) for a given nonlinear system, the control input stabilizing the system can be easily obtained. To find a CLF, the time derivative of an energy function should be negative definite. This procedure frequently requires a control input which is a rational function or includes an inverse function. The control input is not defined on the specific state-space where the denominator of the rational function is equal to 0 or the inverse function does not exist. In this region with singularities, the trajectory of the control system cannot be generated, which is one of the most important reasons why it is hard to make the origin of a nonlinear system be globally asymptotically stable. In this paper, we propose a smooth control law ensuring the globally asymptotic stability by means of cancelling the singularity in the control input.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1151-1154
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• 1993

The purpose of the paper is to explain some heuristic, common sense suppositions of fuzzy control. It is shown that Fuzzy Control is a kind of quasilinear interpolation of prototypes. Control function can be sufficiently exact represented as piecewise-linear function. The best interpolation is connected with normalized intersected fuzzy sets.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.915-927
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• 2008

Networked control systems(NCSs) have gained increasing attention in recent years due to their advantages and potential applications. The network Quality-of-Service(QoS) in NCSs always fluctuates due to changes of the traffic load and available network resources. To handle the network QoS variations problem, this paper presents an intelligent scheduling control method for NCSs, where the sampling period and the control parameters are simultaneously scheduled to compensate the effect of QoS variation on NCSs performance. For NCSs with network-induced delays and packet dropouts, a discrete-time switch model is proposed. By defining a sampling-period-dependent Lyapunov function and a common quadratic Lyapunov function, the stability conditions are derived for NCSs in terms of linear matrix inequalities(LMIs). Based on the obtained stability conditions, the corresponding controller design problem is solved and the performance optimization problem is also investigated. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.10
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• pp.1014-1021
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• 2008

This paper proposes an intelligent sliding mode control method for robotic systems with the unknown bound of model uncertainties. In our control structure, the unknown bound of model uncertainties is used as the gain of the sliding controller. Then, we employ the function approximation technique to estimate the unknown nonlinear function including the width of boundary layer and the uncertainty bound of robotic systems. The adaptation laws for all parameters of the self-recurrent wavelet neural network and those for the reconstruction error compensator are derived from the Lyapunov stability theorem, which are used for an on-line control of robotic systems with model uncertainties and external disturbances. Accordingly, the proposed method can not only overcome the chattering phenomenon in the control effort but also have the robustness regardless of model uncertainties and external disturbances. Finally, simulation results for the five-link biped robot are included to illustrate the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.606-613
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• 2003

As a technical method for controlling chaotic dynamics, this paper presents a predictive control for chaotic systems based on radial basis function networks(RBFNs). To control the chaotic systems, we employ an on-line identification unit and a nonlinear feedback controller, where the RBFN identifier is based on a suitable NARMA real-time modeling method and the controller is predictive control scheme. In our design method, the identifier and controller are most conveniently implemented using a gradient-descent procedure that represents a generalization of the least mean square(LMS) algorithm. Also, we introduce a projection matrix to determine the control input, which decreases the control performance function very rapidly. And the effectiveness and feasibility of the proposed control method is demonstrated with application to the continuous-time and discrete-time chaotic nonlinear system.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.539-545
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• 2011

This paper describes an intelligent service robot system for managing a store in an unmanned environment. The robot can be a good replacement for humans because it is possible to work all day and to remember lots of information. We design a system architecture for configuring many intelligent functions of intelligent service robot system which consists of four layers; a User Interaction Layer, a Behavior Scheduling Layer, a Intelligent Module Layer, and a Hardware Layer. We develop an intelligent service robot 'Part Timer' based on the designed system architecture. The 'Part Timer' has many intelligent function modules such as face detection-recognition-tracking module, speech recognition module, navigation module, manipulator module, appliance control module, etc. The 'Part Timer' is possible to answer the phone and this function gives convenient interface to users.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.24-30
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• 2008

A simulation of hot strip finishing mill automatic gauge control (AGC) system is built, which is divided into four modules such as rolling mill system, AGC module, looper system and strip model. The rolling mill system is built by mechanism modeling, the looper system and strip model are built by function modeling, and the AGC model is tried to use intelligent control of a multi-function AGC system. The target is attempted to use this simulation object to minimize finisher exit strip thickness deviation resulting from strip entry thickness disturbance and rolling force deviation. Simulation results show that the result of this AGC/LPC synthetical system module simulation is quite close to the actual result. The simulation system can also analyze most kinds of disturbance which affect the rolling process. It is proved that the system can represent practical situation of hot strip finishing mill process control, and be used as a basic platform of research and development for researcher and engineer.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.42-45
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• 1998

In this paper, a fuzzy control technique using adjustable scale factors and Lyapunov Function for the precise position control of DC servo system is introduced. The suitable scale factors were selected and the stable control input using the stability theory of Lyapunov function cam be applied. Therefore, the controlled system have the robustness against disturbances and can be stabilized because of reinforced adaptivity. This proposed fuzzy controller is implemented on a 80586 micro-computer which have of fuzzy inference routine part, manipulating part of scale factors and DT-2801 data aquisition board.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.37-40
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• 1997

This paper presents a performance improvement of distributed fuzzy control system by changing the triangular membership function widths according to the input variables. The control region consists of 4 parts according to the sign of error and change of error terms. Each control part is operated by the suitable nonuniform triangular membership function. Through the simulation for the boiler-turbin model of a fossil power plant using decentralized contol, it is verified this proposal