• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.378-384
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• 1993

In this paper, an intelligent adaptive controller is proposed for the process with unmodelled dynamics. The intelligent adaptive controller consists of the numeric adaptive controller and the intelligent tuning part. The continuous scheme is used for the numeric adaptive controller to avoid the problems occurred in the discrete time schemes. The adaptive controller is adopted to the process with time delay. It is an implicit adaptive algorithm based on GMV using the emulator. The tuning part changes the design parameters in the control algorithm. It is a multilayer neural network trained by robustness analysis data. The proposed method can improve the robustness of the adaptive control system because the design parameters are tuned according to the operating points of the process. Through the simulation, robustnesses are shown for intelligent adaptive controller. Finally, the proposed algorithms are implemented on the electric furnace temperature control system. The effectiveness of the proposed algorithm is shown from experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.180.5-180
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• 2001

This paper presents A Design of WMR Controller that being composed of cooperative relation between PID controller and optimized neural network algorithm, it operate a variable control by velocity. Some proposed algorithm in the past just depended on PID controller for the control of position of WMR but for more efficient control we design a variable controller that operate control by PD controller using neural network if it is satisfied with any given condition. it adjust gain of PD controller for real time control using a fast feedforward algorithm which is different with Form of the standard backpropagation algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.6
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• pp.370-479
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• 1988

This paper presents a microprogrammable sequential controller which realizes the sequential logic system with parallel sequences described by a GRAFCET. The proposed controller improves speed, flexibility, programming ease and the efficiency of controlled system by paralle sequencing capability. It is especially designed for complex high speed sequential contollers requiring large I/O capabilities, such as industrial process controller or power electronic conversion controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.6
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• pp.470-470
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• 1988

This paper presents a microprogrammable sequential controller which realizes the sequential logic system with parallel sequences described by a GRAFCET. The proposed controller improves speed, flexibility, programming ease and the efficiency of controlled system by paralle sequencing capability. It is especially designed for complex high speed sequential contollers requiring large I/O capabilities, such as industrial process controller or power electronic conversion controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.3
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• pp.107-113
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• 2001

This paper deals with speed control of DC servo motor using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm. Conventionally a PID controller has been used in the industrial control. But a PID controller should produce suitable parameters for each system. Also, variables of the PID controller should be changed according to environments, disturbances and loads. In this paper described by a experiment that contained a method using a PID controller with a gain tuning based on a Back-Propagation(BP) Learning Algorithm, we developed speed characteristics of a DC servo motor on variable loads. The parameters of the controller are determined by neural network performed on on-line system after training the neural network on off-line system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.67.1-67
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• 2001

This paper presents a neural network based self-tuning fuzzy PI-PD control scheme for robust speed control of induction motor. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PI-PD controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.45.2-45
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• 2001

In case that the perfect model following conditions are not satisfied in the system, a perfect model-following controller is difficult to apply to the system. To deal with this problem, in this paper, a robust imperfect stable model-following controller is designed by combining time delay controller and sliding mode controller based on the concept of two degrees of freedom(2-DOF) controller design method. The experimental dynamic modeling of the commercial overhead crane with capacity of two tons is carried out. To remove the noise of the measuring signals from the swing angle measurement device and estimate the state of the swing angles of the transported object at each time instant, realtime tracker is designed using Kalman filter. The performance of the designed robust controller is tested through the commercial overhead. The experimental results show that the designed controller is robust and applicable to real systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.473-479
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• 2016

This paper describes an accurate and stable current control method of switched reluctance motors(SRMs), which have recently attracted considerable wide attention owing to their favorable features, such as high performance, high durability, structural simplicity, low cost, etc. In most cases, the PI controllers(PICC) have been used mostly for the current control of electric motors because their algorithm and selection of controller gain are relatively simpler compared to other controllers. On the other hand, the PI controller requires an adjustment of the controller gains for each operating point when nonlinear system parameters change rapidly. This paper presents a stable current control method of an SRM using self-tuning fuzzy current controller(STFCC) under nonlinear parameter variation. The performance of the considered method is validated via a dynamic simulation of the current controlled SRM drive using Matlab/Simulink program.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.457-462
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• 2005

Industrial and economical importance of CP(Cellular Phone) is growing rapidly. Combined with IT technology, CP is currently one of the most attractive technologies for all. However, unless we find a breakthrough to the technology, its growth may slow down soon. RT(Robot Technology) is considered one of the most promising next generation technology. Unlike the industrial robot of the past, today's robots require advanced technologies, such as soft computing, human-friendly interface, interaction technique, speech recognition, object recognition, and many others. In this study, we present a new technological concept named RCP(Robotic Cellular Phone), which combines RT & CP, in the vision of opening a new direction to the advance of CP, IT, and RT all together. RCP consists of 3 sub-modules. They are $RCP^{Mobility}$, $RCP^{Interaction}$, and $RCP^{Interaction}$. $RCP^{Mobility}$ is the main focus of this paper. It is an autonomous navigation system that combines RT mobility with CP. Through $RCP^{Mobility}$, we should be able to provide CP with robotic functionalities such as auto-charging and real-world robotic entertainments. Eventually, CP may become a robotic pet to the human being. $RCP^{Mobility}$ consists of various controllers. Two of the main controllers are trajectory controller and self-localization controller. While Trajectory Controller is responsible for the wheel-based navigation of RCP, Self-Localization Controller provides localization information of the moving RCP. With the coordinate information acquired from RFID-based self-localization controller, Trajectory Controller refines RCP's movement to achieve better RCP navigations. In this paper, a prototype system we developed for $RCP^{Mobility}$ is presented. We describe overall structure of the system and provide experimental results of the RCP navigation.

• Journal of Industrial Convergence
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• v.16 no.2
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• pp.33-39
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• 2018

This paper describes the design method of the linear PID controller and proposed the design method in the future. The first PID design method is to ensure phase margin and gain margin. This method guarantees stability by designing in the frequency domain. The second method is an internal model control method. This method is to design the PID controller using the parameters of the internal model after identifying the internal model for the control model. Therefore, this method has a strong disturbance characteristic. Finally, a proposed Cascade and smith-Predictor controller. The combination of the cascade controller and the smith-predator of this method is a controller structure that has two advantages: robust control and optimal control. This method can obtain the performance evaluation index as the optimal controller design method. This PID controller design method becomes the basis of the nonlinear method and is being continuously studied.