• The Pure and Applied Mathematics
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• v.30 no.2
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• pp.191-201
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• 2023

In this paper the control system described by Urysohn type integral equation is studied. It is assumed that control functions are integrally constrained. The trajectory of the system is defined as multivariable continuous function which satisfies the system's equation everywhere. It is shown that the set of trajectories is Lipschitz continuous with respect to the parameter which characterizes the bound of the control resource. An upper estimation for the diameter of the set of trajectories is obtained. The robustness of the trajectories with respect to the fast consumption of the remaining control resource is discussed. It is proved that every trajectory can be approximated by the trajectory obtained by full consumption of the control resource.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.185-189
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• 1987

The controller with robustness described in this paper is designed for processes with variable time-delays. This adaptive mechanism includes servo and stabilizing compensators. In the proposed multivariable controller. knowledge of the system time-delay is not required.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.661-669
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• 1995

This paper presents a design method of dynamic positioning control system in view ofpractical design concept for reliability and robust realization. This method adopts a design method of multivariable robust servo system. The practical experiments of the dynamic positioning control were carried out for a semi-submersible 2-lower hull type platform model with 4 rotatable thrusters in a small water tank. The results fo overall experiment show that the proposed position control method will be an efficient method to the better control performance of dynamic positioning system under serere environment and it is substentially practicable for the platform.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.71-81
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• 2001

This paper analyzes the effectiveness of minimizing vibration and sound transmission on/through a thin rectangular plate by both feedback control and hybrid control which combines adaptive feedforward control with a feedback loop. An experimental system identification technique using the matrix-fractional curve-fitting of the frequency response data is introduced for complex shaped structures. This identification technique reduces the model order o the MIMO(Multi-Input Multi-Output) system which simplifies the practical implementation. The adaptive feedforward control uses a Multiple filtered-x LMS(Least Mean Square) algorithm and the feedback control uses a multivariable digital LQG(Linear Quadratic Gaussian) algorithm. Experimental results show that an effective reduction of sound transmission is achieved by the hybrid control scheme when both vibration and noise measurement signals are incorporated in the controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.33-42
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• 1995

A practical application of a fuzzy-neuro controller is described for an air-conditioning system. Air-handing units are being widely used for improving the performance of central air-conditioning systems. The fuzzy-neuro control system has two controlled variables, temperature and humidity and three control elements, cooling, heating, and humidification. In order to achieve high efficiency and economical contorl, especially in large offices and industrial buildings, two controllable parameters, temperature and humidity, must be adequately controlled by the three final controlling elements. In this paper a fuzzy-neuro control system is described for controlling air-conditioning systems efficiently and economically. Simulation results confirmed that the fuzzy neuro control system is effective for this multivariable system.

• Journal of Power System Engineering
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• v.15 no.1
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• pp.78-85
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• 2011

In order to design the control system of the magnetic bearing for the high speed 3 phase induction motor, the mathematical modeling was conducted and LQ regulator system was designed. When the plant is controllable and detectable, the nominal stability of LQ regulator could be guaranteed. However, LQ regulator doesn't ensure the robustness of stability and performance for the real system because LQ control is the mathematical optimal theory. In this paper to ensure the robustness of stability and performance for the real system, the control systems are designed by the simulation to the variation system parameters and this method was confirmed as an effective means.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.878-883
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• 1991

In this paper, we propose the fuzzy-neural controller which is fuzzy controller with learning ability of neural network. The neural network in this controller is same as the membership function in current fuzzy controller and a parts of inference rules. And, it can be easily extend the control algorithm to multivariable systems. We can show effectiveness of the control algorithm through experiment of the inverted pendulum system.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.209-212
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• 1990

The activated sludge process is a commonly used method for treating sewage and waste waters. The process is characterized by a lack of measurement instrumentations and control goals that are neither well defined nor well understood. In the present study the concept of fuzzy control is employed for such process in which a design method for fuzzy controller based on a multivariable fuzzy reasoning algorithms is investigated and then simulation results are presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1109-1113
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• 1993

A refuse incineration plant is a complex process, whose multi-variable control problems can not be solved conventionally by deriving an exact mathematical model of the process. The usage of advanced fuzzy technologies within the suitable development methodology is demonstrated by a controller implemented for the refuse incineration plant in Hamburg-Stapelfeld, Germany.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.4
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• pp.254-260
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• 2000

This paper deals with the development of fault tolerant control for a nonlinear boiler system with noise and disturbance. The MCMBPC(Multivariable Constrained Model Based Predictive Control) is adopted for the control of the specific boiler turbin model. The fault detection and diagnosis are accomplished with the Kalman filter and two bias estimators. Once a fault is detected, two Bias estimators are driven to estimate the fault and to discriminate Process fault and sensor fault. In this paper, a fault tolerant control scheme combining MCMBPC with a fault compensation method based on the bias estimator is proposed. The proposed scheme has been applied to the nonlinear boiler system and shown a satisfactory performance through some simulations.