• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.223-226
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• 1991

In this paper, the problem of designing on adaptive controller for dc drives using state observers, which is operated under varying load conditions, is addressed. A robust self-tuning controller that can track a constant reference and reject constant load disturbances is also studied. This scheme is very attractive since the estimates of system parameters are available in real time. Parameter estimation is based on the recursive least squares method and the control algorithm of the pole placement technique. Also, state observer systems are applied. State observer systems are required to estimate the states quickly and exactly without being affected by the disturbances.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.69-71
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• 1997

The direct drive motor is directly coupled by load. So, it is directly affected by load and disturbances. To control the direct drive motor, a robust controller is need. The main feature of variable structure system is that system trajectories are robust and insensitive to parameter variations and disturbances in the sliding mode. In this paper, adaptive variable structure controller, is used for the BLDD SM(Brushless Direct Drive Servo Motor) control. The chattering problem is reduced by using the saturation function.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.2
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• pp.80-88
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• 2005

In this paper, an robust adaptive backstepping controller is proposed for the speed control of separately excited DC motor with uncertainties and disturbances. Armature and field resistance, damping coefficient and load torque are considered as uncertainties and noise generated at applying load torque to motor is also considered. It shows that the backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation and experiment results are provided to demonstrate the effectiveness of the proposed controller.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.883-885
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• 1993

This paper presents a integral-augumented nonlinear sliding surface without a reaching phase. The conventional linear sliding surface has reaching phase, and sliding mode can't realized during this phase, the trajectories may he sensitive to the load disturbances. An proposed algorithm does not have reaching phase, so robust to the load disturbances.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.335-341
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• 1998

In this study, the dynamic characteritics in various loading methods for wear tester were investigated experimentally. As for the dead-weight, the pneumatic, and the hydraulic method, the load control performance against external disturbances was estimated under the several loading conditions like the different sliding speed, the varied normal load, and the misaligument. The hydraulic loading method showed the most stable loading performance of all the loading methods in the experiment.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.363-365
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• 2002

The characteristic responds of load respect to various disturbances which can usually be occurred on actual power system is very important to analyze performance and to improve load with high-technology. The disturbance power supply is designed to provide wide range of power to testing load. This device uses PLC technology to dynamic characteristic experiment and CVVF to change frequency. Also this instrument includes data acquisition system to obtain reliable data from experiment.

• Environmental Engineering Research
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• v.12 no.5
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• pp.197-200
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• 2007

Advanced control is getting increasingly demanded in water and wastewater treatment systems. Various case studies have shown significant savings in operating costs, including energy costs, and remarkably short payback times. It has been demonstrated that instrumentation, control and automation (ICA) may increase the capacity of biological nutrient removing wastewater treatment plants by 10-30% today. With further understanding and exploitation of the mechanisms involved in biological nutrient removal the improvements due to ICA may reach another 20-50% of the total system investments within the next 10-20 years. Disturbances are the reason for control of any system. In a wastewater treatment system they are mostly related to the load variations, but many disturbances are created also within the plant. In water supply systems some of the major disturbances are related the customer demand as well as to leakages or bursts in the pipelines or the distribution networks. Hardly any system operates in steady state but is more or less in a transient state all the time. Water and energy are closely related. The role of energy in water and wastewater operations is discussed. With increasing energy costs and the threatening climate changes this issue will grow in importance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.42-46
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• 2012

With the development of industry, more large-scale non-linear loads are added to existing power systems and they cause the serious power quality (PQ) problems to the nearby sensitive installations more and more. To protect the important loads and mitigate the impact of PQ disturbances on them, various compensating devices are installed. One of the most important control skills used in the compensating equipment at the load side is how fast they can recognize or detect the discontinuous abnormal PQ events from the normal voltage signal. This paper deals with two estimation methods for the fast detection and tracking of general PQ disturbances: Teager Energy Operator (TEO), which is a non-linear operator and used for a short time energy calculation, and Kalman Filter (KF), which is one of the most universally used estimation techniques. And it is also shown how to apply the TEO and the KF to detect the PQ disturbances such as voltage sag, swell, interruption, harmonics and voltage fluctuation.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.3
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• pp.321-328
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• 1998

When we control the level of the steam generator in the nuclear power plants, a swell and shrink arises from many disturbances such as feed water rate, feed water temperature, main steam flow rate, and coolant temperature. If we use the conventional type of PI controller in this system, we will not have stability during controlling at lower power, the removal function of disturbances, and a load follow-up control effectively. In this paper, we study the application of a 2-Degree of Freedom(2-DOF) PID controller to the level control of the steam. generator of nuclear power plants through the simulation and the experimental steam generator. We use the parameters $\alpha$, $\beta$, $\gamma$ of the 2-DOF PID controller for the removal of disturbances and the parameters Kp,Ti,Td of the conventional type of PID controller for controlling setpoint. The back-propagation learning algorithm of neural network is used for tuning the 2-DOF PID controller. We can find satisfactory results of the removal of the disturbances and the tracking function in the change of setpoint through the simulation and experimental steam generator.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.5
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• pp.503-511
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• 1997

In 3 phase induction motor control system, the speed control using the load torque observer becomes robust against disturbances by means of a feed-forward control of the estimated load torque component. In case of variation of inertia moment, the estimated load torque has error because the observer uses the nominal inertia to estimate the load torque. And so, it is difficult to obtain good speed control characteristics. This paper has two study target strategy. First, we executes feed-forward control with the load torque observer when motor inertia has nominal value and compare it with conventional PI con¬trol. The second strategy estimates inertia moment error using the load torque observer when inertia moment change. The proposed two strategy is confirmed through the computer simulations and the experimental implementations by TMS320C31 microprocessor.