• Structural Engineering and Mechanics
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• v.27 no.5
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• pp.527-540
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• 2007

The modal controller of single-input system cannot stabilize the defective system with positive real part of repeated eigenvalues, because some of the generalized modes are uncontrollable. In order to stabilize the uncontrollable modes with positive real part of eigenvalues, the multi-input system should be introduced. This paper presents a recursive procedure for designing the feedback controller of the multi-input system with defective repeated eigenvalues. For a nearly defective system, we first transform it into a defective one, and apply the same method to manage. The proposed methods are based on the modal coordinate equations, to avoid the tedious mathematic manipulation. As an application of the presented procedure, two numerical examples are given at end of the paper.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.3
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• pp.21-26
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• 2010

This paper deals with the precise parameter estimation of an air vehicle without a priori information. First, Recursive Least Squares technique, which is an equation error method and does not require any a priori information, is applied and then the extended Kalman filter is used to tune parameters more precisely. To show the performance, a nonlinear longitudinal missile model is simulated and the parameters are estimated. The results show that this consecutive application of the techniques gives a very good estimation performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.5
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• pp.12-25
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• 1994

A two dimensional constant geometry FFT algorithms and architectures with shuffled inputs and normally ordered outputs are presented. It is suitable for VLSI implementation because all buterfly stages have identical, regular structure. Also a methodology using shuffled FFT inputs and outputs to halve the number of butterfly stages connected by a global interconnection which requires much area is presented. These algorithms can be obtained by shuffling the row and column of a decomposed FFT matrix which corresponds to one butterfly stage. Using non-recursive and recursive pipeline, the degree of serialism and parallelism in FFT computation can be adjusted. To implement high performance high radix FFT easily and reduce the amount of interconnections between stages, the method to build a high radix PE with lower radix PE 's is discussed. Finally the performances of the present architectures are evaluated and compared.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1234-1238
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• 2004

A Controlled neural networks are proposed in order to measure nonlinear environments in adaptive and in realtime. The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between tile output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models. To show the performance of this one, we have various experiments. And this controller call prove effectively to be control in the environments of various systems.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.8-15
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• 1999

One of the main reason advocating redundant manipulators' superiority in application is that they can afford to optimize a dexterity measure, for example the manipulability measure. However, to obtain the gradient of the manipulability is not an easy task in case of general manipulator with high degrees of redundancy. This article proposes a method to compute the gradient of the manipulability, based on recursive algorithm to compute the Jacobian and its derivative using Denavit-Hartenberg parameters only. To characterize the null motion of redundant manipulators, the null space matrix using square minors of the Jacobian is also proposed. With these capabilities, the inverse kinematics of a redundant manipulator system can be done automatically. The result is easily extended to dual manipulator system using the relative kinematics.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.76-83
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• 2001

In this study, the static and dynamic characteristics of turning process was modelled and the analytic realization of regen-erative chatter mechanism was discussed. In this regard, we have discussed on the comparative assessment of recursive times series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision turning operation. In this study, simulation and experimental work were performed to show the malfunction behaviors. For this purpose, new Recursive Extended Instrument Variable Method(REIVM) was adopted for the on-line system identification and monitoring of a machining process. Also, we can apply REIVE algorithms in real process for the detection of chatter frequency and dynamic property and analyze the stability lobe of the system by changing a parameter of cutting dynamics in regenerative chatter mechanics, if it is stable or unstable, Also, The stability lobe of chatter was analysed.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.110-117
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• 1995

This study presents and algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is applied for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm was tested on a check weigher. Discussions were extended to the development of noise reduction techniques and to the lagged introduction of objects on the moving plate. It turns out that the algorithm shows several desirable features suitable for real-time signal processing with a microcomputer, which are high precision and stability in noisy environment.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.70-79
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• 2013

In this paper, a comparative study on the frequency estimation methods using IRDWT (Improved Recursive Discrete Wavelet Transform), FRDWT(Fast Recursive Discrete Wavelet Transform), and GCDFT(Gain Compensator Discrete Fourier Transform) is presented. The 345[kV] power system modeling data of the Republic of Korea by EMTP-RV is used to evaluate the performance of the proposed two kinds of RDWT(IRDWT and FRDWT) and GCDFT. The simulation results show that the frequency estimation technique based on FRDWT could be the optimal frequency measurement method, and thus can be applied to FDR(Fault Disturbance Recorder) for wide-area blackout protection or frequency measurement apparatus.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.525-526
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• 2008

For measuring nonlinear Vehicle Modeling based on 7-Depth Sensor, the neural networks are proposed m adaptive and in realtime. The structure of it is similar to recurrent neural networks; a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by backpropagation and each weights are updated by RLS(Recursive Least Square). Consequently, this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. This new neural networks is Error Estimated Neural Networks. We can estimate nonlinear models in realtime by the proposed networks and control nonlinear models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.521-526
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• 2009

In this paper, a complex-valued recursive least squares escalator filter algorithm with reduced computational complexity for complex-valued signal processing applications is presented. The local tap weight of RLS-ESC algorithm is updated by incrementing its old value by an amount equal to the local estimation error times the local gain scalar, and for the gain scalar, the local input autocorrelation is calculated at the previous time. By deriving a new gain scalar that can be calculated by using the current local input autocorrelation, reduced computational complexity is accomplished. Compared with the computational complexity of the complex-valued version of RLS-ESC algorithm, the computational complexity of the proposed method can be reduced by 50% without performance degradation. The reduced computational complexity of the proposed algorithm is even less than that of the LMS-ESC. Simulation results for complex channel equalization in 64QAM modulation schemes demonstrate that the proposed algorithm has superior convergence and constellation performance.