• Proceedings of the KAIS Fall Conference
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• 2010.11a
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• pp.341-343
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• 2010

The parameters of PID controller should be readjusted whenever system character change. In spite of a rapid development of control theory, this work needs much time and effort of expert. In this paper, to resolve this defect, after the sample of parameters in the changeable limits of system character is obtained, these parametrs are used as desired values of back propagation learning algorithm, also neural network auto tuner for PID controller is proposed by determing the optimum structure of neural network. Simulation results demonstrate that auto-tuning proper to system character can work well.

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.49-52
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• 1988

This paper deal with the robust high gain controller design technique by inner-loop feedback, output feedback, feedforward compensation, and presented the algorithm to be required the determination of gain matrix. Using this control scheme, simulation results have bean tested for the linearized model of the aircraft.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.275-280
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• 2005

The principal context of this research is the approach to an artificial neural network algorithm which solves multivariable nonlinear equation systems by estimating the state of line power flow. First a dynamical neural network with feedback is used to find the minimum value of the objective function at each iteration of the state estimator algorithm. In second step a two-layer neural network structures is derived to implement all of the different matrix-vector products that arise in neural network state estimator analysis. For hardware requirements, as they relate to the total number of internal connections, the architecture developed here preserves in its structure the pronounced sparsity of power networks for which state the estimator analysis is to be carried out. A principal feature of the architecture is that the computing time overheads in solution are independent of the dimensions or structure of the equation system. It is here where the ultrahigh-speed of massively parallel computing in neural networks can offer major practical benefit.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.282-284
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• 1992

In this paper, we deal with design method of two-degree-of-freedom control system which desired property of robustness and tracking can be achieved simultaneously, Controller is designed by means of model matching method and H$\infty$ weighted sensitivity minimization design method. Satisfactory result of design example is obtained by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.33.5-33
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• 2001

We consider here the problem of spectral estimation of multidimensional wide sense stationary (WSS) random process. A method, employing a special difference equation of correlation function, is proposed to solve the problem of multidimensional spectral estimation. In this approach, the special difference equation of correlation function is derived by modal decomposition method. Maximum likelihood estimator and Kalman filter are used to estimate the model parameters of the difference equation and the decomposed spectral residues. An algorithm is presented to estimate the multidimensional spectral density. According to the result of the simulation, these methods are feasible to estimate the spectral density of WSS process, which is realized by finite dimensional multivariable lineal system driven by white noise.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.871-878
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• 2003

With the development of micro -technology, the demand for micro actual ing device is increasing. But, it is difficult to achieve high resolution and wide bandwidth with the conventional contact systems. So, the contact-free systems which are suspended or levitated by magnetic force or air bearing were proposed. These systems can be applied to high precision stages and alignment apparatuses. This paper describes a magnetically suspended system with four degrees of freedom which are composed of three rotations (roll, pitch, yaw), and one translation ( z). The operating principle and the structure of the system are similar to variable reluctance type electric machines. In this study, the force analysis is executed using magnetic circuit and virtual work principle, and the equations that describe the dynamics of the system are presented. The multivariable PID controller is adapted to the system and the experiment is executed.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.502-506
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• 1992

In this study, we proposed the fuzzy modeling method and designed a model-based logic controller for Activated and Sludge Process(A.S.P.) in sewage treatment. The identification of the structure of fuzzy implications is carreid out by use of fuzzy c-means clustering algorithm. And to identify the parameters of fuzzy implications, we used the complex and the least square method. To tune the premise parameters automatically the complex method is implemented. The model-based fuzzy controller is designed by rules generated from the identified A.S.P. fuzzy model. The feasibility of the proposed approach is evaluated through the identification of the fuzzy model to describe an input-output relation of the A.S.P.. The performance of identified model-based fuzzy controller is evaluated through the computer simulations.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.9 s.186
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• pp.84-91
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• 2006

The synthesis of optimal controllers for multivariable systems usually requires an accurate linear model of the plant dynamics. Real systems, however, contain nonlinearities and high-order dynamics that may be difficult to model using conventional techniques. This paper presents a novel loaming method for the synthesis of LQR controllers that doesn't require explicit modeling of the plant dynamics. This method utilizes the sign of Jacobian and gradient descent techniques to iteratively reduce the LQR objective function. It becomes easier and more convenient because it is relatively very easy to get the sign of Jacobian instead of its Jacobian. Simulations involving an overhead crane and a hydrofoil catamaran show that the proposed LQR-LC algorithm improves controller performance, even when the Jacobian information is estimated from input-output data.

• 전기의세계
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• v.23 no.2
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• pp.46-54
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• 1974

The purposes of this paper are to deal with the design of m-input, m-output linear systems by the state variable feedback, and to extend the design capability of the state variable feedback design. The design requirements are decoupling and the exact realigation of desired transfer functions. Some methods are proposed to insert series compensators in the fixed plant in the cases when series compensators are needed to meet the input-output transfer matrix specification. The method for adding series compensators to the input channels of the fixed plant is shown by examples to lead both to the loss of the ability to decouple the augmented plant by the state variable feedback, and to the loss of desired zeroes. A method which avoids these two hazards is developed in which series compensators are put on the output channels of the fixed plant: it is proved that the augmented plant is F-invariant. By treating each subsystem individually, the designer can apply some of the previous developed knowledge of the state variable design of single-input, single-output systems.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.2
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• pp.199-209
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• 1990

In this paper, a multivariable robust controller for a boiler-burbine system is designed by using a modified LQG/LTR method. From the known nonlinear dynamic model, a linearized model is obtained with the saturations at both input magnitude and input varying rate. The modeling error is analyzed at various operation points. A new dynamics augmentation method in the LQG/LTR method is suggested which can be applied to LQG/LTR method to reject the input and output disturbances and to follow reference inputs under modeling errors. The good performance of the designed controller is shown by simulations in various conditions.