• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.73-78
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• 1999

This paper presents an effective construction method of adaptive multiple control systems utilizing some knowledge upon the plants. The adaptive multiple control system operates plants un-der widely changing environmental conditions. The adaptive multiple control system is composed of a family of candidate controllers together with a supervisor. The system does not require any identification schemes of environmental conditions. Monitoring outputs of the plant, the supervisor switches from one candidate controller to another, The basic ideas of adaptation are as follows: (1)each candidate controller is prepared for each environmental condition in advance; (2)the supervise. applies a sequence of speculative controls to the plant with candidate controllers just after the start of control or just after the detection of a change in the environmental condition. Each candidate controller can keep the system stable during one-step period of the speculative control and the most appropriate candidate controller for the environmental condition to which the system is exposed can be selected before the last trial of speculative control step comes to an end. We proposed a construction method of adaptive multiple control system without any knowledge of plant dynamics and applied the method to a cart-pole balancing problem and a vehicle anti skid braking system. In real applications, as we can often easily obtain a piece of knowledge upon plant dynamics beforehand, we intend to extend the method such that multiple control systems can be efficiently designed using the knowledge. We apply the new idea to the cart-pole balancing problem with variable length of the pole. The simulation experiments lead us to the conclusion that the new attempt can reduce the manpower to design the candidate controllers for adaptive multiple control systems.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.2
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• pp.20-30
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• 2001

In the paper, we propose a predictive control scheme using multiple neural network-based prediction models. To construct the multiple models, we select several specific values of a parameter whose variation affects serious control performance in the plant. Among the multiple prediction models, we choose one that shows the best predictions for future outputs of the plant by a switching technique. Based on a nonlinear programming method, we calculate the current process input in the nonlinear predictive control system with multiple prediction models. The proposed control method is shown to be very effective when a parameter of the plant changes or the time delay, if it exists, varies. It is also shown that the proposed method is successfully applied for the control of suspension in a electro-magnetic levitation system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1470-1473
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• 2003

In this paper the networked control systems (NCS) problem is discussed where plants and controllers are distributed and interconnected by a common network. NCS is designed with LQ regulator and applied to an inverted pendulum accounting for the multiple time delays. We are to deals with a networked control system with a single controller, multiple sensors and multiple actuators. Since these parts are distributed, they are interconnected by communication networks. An NCS with LQ regulator is designed and applied to an inverted pendulum as a benchmark plant to check its performance under time delays induced by the network. Network induced delays are composed of two parts. One is the delay from controller to plant, and another is from plant to controller. They are assumed to be constant in this paper, and the plant and controller are discretized. To apply the LQ regulator the NCS model is transformed to a standard model with delayed states as state variable. And real network induced delay is measuring in TCP/IP network assuming that two delays are constant.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1100-1103
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• 1996

A well-known problem in adaptive control is the poor transient response which is observed when adaptation is initiated. This paper proposes a useful method to improve the transient response of adaptive control systems by using multiple models of the plant and switching mechanism by fuzzy inference. The models are identical except for initial estimates of the unknown plant parameteres. The control input to be applied is determined at every instant by the model which best approximates the plant. Simulation results are presented to indicate the performance improvement of adaptive control systems using the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.110.4-110
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• 2002

In practical control area, there are many examples with multiple objectives which may conflict or compete with each other like overhead crane control, automatic train operation, and refuse incinerator plant control, etc. These kinds of control problems are called multiobjective control problems, where it is difficult to provide the desired performance with control strategies based on single-objective optimization. Because the conventional control theories usually treat the control problem as the single objective optimization problem , the methods are not adequate to treat the multiobjective control problems. Particularly, in case of large scale systems or ill-defined systems, the multiple obj..

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.51-57
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• 2014

This paper presents a synchronizing adaptive feedforward control for clamping servomechanism of injection molding machines. Based on MBS, virtual design model has been developed for a direct forcing clamping mechanism. A synchronizing controller is designed and combined with adaptive feedforward control to accommodate mismatches between the real plant and the linear plant model used. From tracking control simulations, it is shown that significant reduction in position tracking error is achieved through the use of proposed control scheme.

• Journal of the Semiconductor & Display Technology
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• v.8 no.2
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• pp.37-42
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• 2009

This paper presents an idea of implementation of many semiconductor equipments. The idea is a new design methodology of the Networked Control Systems (NCSs) using CAN (Controller Area Network) will be discussed. The Distributed Control Systems (DCSs) is very useful to control multiple systems that have a distance to communicate. The CAN protocol is very strong to noise, also provides the user with many powerful functionality. Only one communication line (BUS) is used, so that a control and a maintenance of those systems are very easy. This paper is concerned with the speed control of multiple DC motors using CAN Protocol. Experimental systems are made to validate effectiveness of the systems. The results of the experiment show that the NCSs using CAN has excellency in real time control.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.87-87
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• 2000

In this paper, an integrated design of fault detection, diagnosis and reconfigurable control tot multi-input and multi-output system is proposed. It is based on the interacting multiple model estimation algorithm, which is one of the most cost-effective adaptive estimation techniques for systems involving structural and/or parametric changes. This research focuses on the method to recover the performance of a system with failed actuators by switching plant models and controllers appropriately. The proposed scheme is applied to a fault tolerant control design for flight control system.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.817-826
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• 1987

An offset-free self-tuning control with pole placement (STCPP) and a recursive parameter estimation with multiple and variable forgetting factors (REWF), together with their application to a real plant, are described. There are two different types of offset-free STCPP; their features are analysed and discussed. REMVF employs as many forgetting factors as parameter estimates. It is suitable when parameters to be estimated are changing at different rates. The offset-free STCPP and REMVF have been successfully applied to a real plant, giving excellent results.

• Journal of Bio-Environment Control
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• v.23 no.1
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• pp.11-18
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• 2014

To investigate the influence of surrounding environment on the plant temperature and examine the effect of plant temperature control by fogging and airflow, plant temperature of tomato, inside and outside air temperature and relative humidity, solar radiation and wind speed were measured and analyzed under various experimental conditions in plastic greenhouse with two-fluid fogging systems and air circulation fans. According to the analysis of plant temperature and the change of inside and outside air temperature in each condition, inside air temperature and plant temperature were significantly higher than outside air temperature in the control and shading condition. However, in the fogging condition, inside air temperature was lower or slightly higher than outside air temperature. It showed that plant temperature could be kept with the temperature similar to or lower than inside air temperature in fogging and airflow condition. To derive the relationship between surrounding environmental factor and plant temperature, we did multiple regression analysis. The optimum regression equation for the temperature difference between plant and air included solar radiation, wind speed and vapor pressure deficit and RMS error was $0.8^{\circ}C$. To investigate whether the fogging and airflow contribute to reduce high temperature stress of plant, photosynthetic rate of tomato leaf was measured under the experimental conditions. Photosynthetic rate was the highest when using both fogging and airflow, and then fogging, airflow and lastly the control. So, we could assume that fogging and airflow can make better effect of plant temperature control to reduce high temperature stress of plant which can increase photosynthetic rate. It showed that the temperature difference between plant and air was highly affected by surrounding environment. Also, we could estimate plant temperature by measuring the surrounding environment, and use it for environment control to reduce the high temperature stress of plant. In addition, by using fogging and airflow, we can decrease temperature difference between plant and air, increase photosynthetic rate, and make proper environment for plants. We could conclude that both fogging and airflow are effective to reduce the high temperature stress of plant.