• Proceedings of the KSME Conference
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• 2007.05a
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• pp.915-920
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• 2007

A new optimal state feedback and disturbance feedforward control design in the sense of minimizing $L_{2}-gain$ from disturbance to control output is proposed for disturbance attenuation of systems with bounded control input and measurable disturbance. The controller is derived in the framework of linear matrix inequality(LMI) optimization. A gain scheduled state feedback and disturbance feedforward control design is also suggested to improve disturbance attenuation performance. The control gains are scheduled according to the proximity to the origin of the state of the plant and the magnitude of disturbance. This procedure yields a stable linear time varying control structure that allows higher gain and hence higher performance controller as the state and the disturbance move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.11
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• pp.59-65
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• 2007

A new optimal state feedback and disturbance feedforward control design in the sense of minimizing $L_2$-gain from disturbance to control output is proposed for disturbance attenuation of systems with bounded control input and measurable disturbance. The controller is derived in the framework of linear matrix inequality(LMI) optimization. A gain scheduled state feedback and disturbance feedforward control design is also suggested to improve disturbance attenuation performance. The control gains are scheduled according to the proximity to the origin of the state of the plant and the magnitude of disturbance. This procedure yields a stable linear time varying control structure that allows higher gain and hence higher performance controller as the state and the disturbance move closer to the origin. The main results give sufficient conditions for the satisfaction of a parameter-dependent performance measure, without violating the bounded control input condition.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.39-42
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• 2002

For the purpose of modeling EEG signal which has nonstationary and nonlinear dynamic characteristics, this paper propose a state feedback real time recurrent neural network model. The state feedback real time recurrent neural network is structured to have memory structure in the state of hidden layers so that it has arbitrary dynamics and ability to deal with time-varying input through its own temporal operation. For the model test, Mackey-Glass time series is used as a nonlinear dynamic system and the model is applied to the prediction of three types of EEG, alpha wave, beta wave and epileptic EEG. Experimental results show that the performance of the proposed model is better than that of other neural network models which are compared in this paper in some view points of the converging speed in learning stage and normalized mean square error for the test data set.

• 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.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.356-362
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• 2002

In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.523-525
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• 2006

Adaptive neural state-feedback controllers for the fully nonaffine pure-feedback nonlinear system are presented in this paper. By reformulating the original pure-feedback system to a standard normal form with respect to newly defined state variables, the proposed controllers require no backstepping design procedures. Avoiding backstepping makes the controller structure and stability analysis considerably to be simplified. The proposed controllers employ only one neural network to approximate unknown ideal controllers, which highlights the simplicity of the proposed neural controller.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4E
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• pp.31-36
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• 1999

Circulant Feedback Delay Networks (CFDN's), whose feedback matrix is circulant to control the stability of system and time-frequency response easier than unitary one, were recently proposed. However, the drawback of this structure is that the flatness of the frequency response of CFDN's is not enough and it is difficult to adjust the placement of zeros to decrease this problem. Therefore, we propose Modified CFDN's (MCFDN's) consisted of a general recursive filter and CFDN's to maintain maximally the impulse response of CFDN's and improve the flatness of frequency response without adjusting the placement of zeros. The delay unit of a general recursive filter's feedback loop is replaced by CFDN's, are omitted the direct path. We represent the usefulness of MCFDN's to build artificial reverberators and the main parameter to determine characteristics of MCFDN's in this paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.260-269
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• 2000

The fuzzy and state-feedback control systems have been applied in various areas from non-linear to linear systems. A Fuzzy controller is endowed with control rules and membership function that are constructed on the knowledge of expert, as like intuition and experience. but It is very difficult to obtain the exact values which are the membership function and consequent parameters. though apply back-propagation algorithm to the system, the convergence time a much. Besides, the state-feedback system is most widely used in industry due to its simple control structure and easily able to design the controller. but it is weak in complex system of higher degree and non-linear. In this paper presents the design of a fuzzy switching mode, it these two controllers work at different operation conditions, the advantages of both controller can be retained and the disadvantages can be removed. Between the Fuzzy and the State-feedback controlles, the good outputs are selected by the switching mode. Moreover it is powerful in complex system of higher degree and non-linear. In these sense compared with the state-feedback controller, the performance of the proposed controller was improvedin the section of linearization.

• Journal of Power Electronics
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• v.14 no.5
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• pp.1028-1037
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• 2014

To optimize controller design and improve static and dynamic performances of three-phase four-leg inverter systems, a compound control method that combines state feedback and quasi-sliding mode variable structure control is proposed. The linear coordinate change matrix and the state variable feedback equations are derived based on the mathematical model of three-phase four-leg inverters. Based on system relative degrees, sliding surfaces and quasi-sliding mode controllers are designed for converted linear systems. This control method exhibits the advantages of both state feedback and sliding mode control. The proposed controllers provide flexible dynamic control response and excellent stable control performance with chattering suppression. The feasibility of the proposed strategy is verified by conducting simulations and experiments.

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.238-247
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• 2005

In this Paper. we Presents subband design techniques of a compensating filter and adaptive feedback canceller for the digital hearing aid. The sensorineural hearing loss has a hearing threshold that shows a nonlinear characteristic in frequency domain. and its compensation suffers from an echo that produced by an undesired time varying feedback path. Therefore. the digital hearing aid requires the compensator that can adjust gains nonlinearly in frequency bands and eliminate the echo rapidly In the Proposed digital hearing aid. the compensating filter is designed by the adaptive system identification method in subband structure, and the adaptive feedback canceller is designed by the subband affine projection algorithm. The designed compensation filter can control the nonlinear gain in each subband respectively, therefore precise compensation is possible. And the feedback canceller using the subband adaptive filter achieves fast convergence rate. The Performances of the Proposed method are verified by computer simulations as comparing with the behaviors of the previous trials.