• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.4
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• pp.293-300
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• 1987

This paper presents a desing of a PWM programmable controller for industrial robot to be utilized in process which reqires various movements and repeating operations. To be specific, a low-level robot language is constructed which makes easy for the user to program complex robot motion, and an interpreter is developed to execute the program. Also, related hardware and software, and monitor program for convenience of user are implemented. When the proposed controller is applied to the catresian coordinate 4-axis manipulator, it reveals that the error probabilities of X,Y and Z axis as 0.033%, 0.023%,0.028% respectively.

• Proceedings of the KAIS Fall Conference
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• 2006.05a
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• pp.344-347
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• 2006

This paper proposes an optimum tuning which improves the tuning effect of IMC-PID and guarantees the performance and robustness of controller system by considering gain margin, phase margin, sensitivity functions and integral square error(ISE) for IMC-PID controller.

• International Journal of Air-Conditioning and Refrigeration
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• v.14 no.4
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• pp.138-146
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• 2006

Recently, a technology based on the proportional integral (PI) control have grown rapidly owing to the needs for the robust capacity of the controllers from industrial building sectors. However, PI controller generally requires tuning of gains for optimal control when the outside weather condition changes. The present study presents the possibility of reinforcement learning (RL) control algorithm with PI controller adapted in the HVAC system. The optimal design criteria of RL controller was proposed in the environment chamber experiment and a theoretical analysis was also conducted using TRNSYS program.

• IE interfaces
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• v.9 no.1
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• pp.25-40
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• 1996

It is a time-consuming work to develop a control software for AGVS considering different physical arrangements and transport requirements in automated manufacturing systems. An integrated software environment is suggested to support the development of the control software by utilizing a simulation software which imitates changes in the target shop floor. First, the basic functions of the controller are defined and interactions between modules(function) are identified to enhance the modularity of the controller. Prototype software is developed for the simulation station and the control station, respectively, which are connected with each other by a communication link to transmit predefined messages.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.491-493
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• 2007

This paper is suggesting the method to embody Multi-Axes robot controller by using CAN which has been the most popular industrial networks. The robot controller guarantees the efficiency and reliability by using CAN as a communication tool between upper robot control parts and lower control parts.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.144-146
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• 1998

In this study Dead time equivalent resistance of Voltage source power converter is very important in current controller design. And Non-linear Modeling method can be applied in Power converter analysis. Using Describing Function method and Non-linear Resistance Modeling. Voltage Source Power Converter Bode diagram and Current controller analysis method are more reality.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.546-551
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• 2004

In this paper, a level controller is designed with the neuro-fuzzy model based on Takagi-Sugeno fuzzy system. The fuzzy system is employed as the controller, which can be tuned by the neural network mechanism based on a gradient descent technique. The tuning mechanism will provide an optimal process input by forcing the process error to zero. The proposed controller provides the online tunable mode to adjust the consequent membership function parameters. The controller is implemented with M-file and graphic user interface (GUI) of Matlab program. The program uses MPIBM3 interface card to connect with the industrial processes In the experimentation, the proposed method is tested to vary of the process parameters, set points and load disturbance. Processes of one tank and two tanks are used to evaluate the efficiency of our controller. The results of the both processes are compared with two PID systems that are 3G25A-PIDO1-E and E5AK of OMRON. From the comparison results, our controller performance can be archived in the case of more robustness than the two PID systems.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.85-89
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• 2004

Robust control for feedback control system is needed according to the highest precision of industrial automation. However, when a neural network feedback control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem, in this paper, hybrid control method of neural network controller and PID controller is presented. A neural network controller is operated as a main controller, a PID controller is a assistant controller which operates only when some undesirable phenomena occur, e.q., when the error hit the boundary of constraint set. The robust control function of neural network-PID hybrid controller is demonstrated by speed control of Motor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.1
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• pp.112-115
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• 2003

Robust control for servo control system in needed according to the highest precision of industrial automation. However, when a servo control system has an effect of disturbance, it is very difficult to guarantee the robustness of control system. As a compensation method solving this problem in this paper, Hybrid control method of Main controller(PIU)-Differential Supervisory controller is presented. Main controller is operated as a feedback controller. Differential Supervisory controller as a assistant controller is operated when state in unstable disturbance. The robust control function of Differential Supervisory controller is demonstrated by Speed control of Motor.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1255-1262
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• 2012

Look into the nuclear power plant of Wolsong currently, it is controlled in order to required operating pressure with PI controller. PI controller has a simple structure and satisfy design requirements to gain setting. However, It is difficult to control without changing the gain from produce changes in parameters such as loss of the valves and the pipes. To solve these problems, the dynamic change of the PI controller gain, or to compensate for the PI controller output is desirable to configure the controller. The aim of this research and development in the parameter variations can be controlled to a stable controller design which is reduced an error and a vibration. Proposed PI/NN control techniques is the PI controller and the neural network controller that combines a parallel and the neural network controller part is compensated output of the controller for changes in the parameters were designed to be robust. To directly evaluate the controller performance can be difficult to test in real processes to reflect the characteristics of the process. Therefore, we develope the simulator model using the real process data and simulation results when compared with the simulated process characteristics that showed changes in the parameters. As a result the PI/NN controller error and was confirmed to reduce vibrations.