• Journal of Institute of Control, Robotics and Systems
• /
• v.4 no.5
• /
• pp.636-643
• /
• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• Proceedings of the KIEE Conference
• /
• 2002.11b
• /
• pp.85-87
• /
• 2002

The paper describes the formulation of state matrix equations from the linearized multi-machine power system including network dynamics and the application of IEEE First Benchmark Model. The eigenvalues of IEEE First Benchmark Model are investigated not only by changing the compensation of series capacitance at no-load conditions, but also by varying the generator loading at fixed compensation of capacitance. In addition, the pure electrical self-excited mode is also examined by an eigen analysis and time domain simulation.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.3
• /
• pp.447-457
• /
• 1994

This paper presents a compensation method for discrete-time control systems with saturation nonlinearities to cope with the reset windup phenomena. The proposed ARW (Anti-Reset Windup) method is motivated by the concept of the equilibrium point. The design parameter of the ARW scheme is explicitly derived by minimizing a reasonable performance index. The resulting dynamics of the compensated controller exhibits the reduced model form of the unsaturated system which can be obtained by the singular perturbational model reduction method. An example is given to illustrate the effectiveness of the proposed method.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.7
• /
• pp.603-611
• /
• 2003

This paper proposes an effective feature compensation scheme based on speech model for achieving robust speech recognition. Conventional model-based method requires off-line training with noisy speech database and is not suitable for online adaptation. In the proposed scheme, we can relax the off-line training with noisy speech database by employing the parallel model combination technique for estimation of correction factors. Applying the model combination process over to the mixture model alone as opposed to entire HMM makes the online model combination possible. Exploiting the availability of noise model from off-line sources, we accomplish the online adaptation via MAP (Maximum A Posteriori) estimation. In addition, the online channel estimation procedure is induced within the proposed framework. For more efficient implementation, we propose a selective model combination which leads to reduction or the computational complexities. The representative experimental results indicate that the suggested algorithm is effective in realizing robust speech recognition under the combined adverse conditions of additive background noise and channel distortion.

• The Journal of the Acoustical Society of Korea
• /
• v.16 no.5
• /
• pp.112-121
• /
• 1997

In this paper, we study a model parameter compensation method for noise-robust speech recognition. We study model parameter compensation on a sentence by sentence and no other informations are used. Parallel model combination(PMC), well known as a model parameter compensation algorithm, is implemented and used for a reference of performance comparision. We also propose a modified PMC method which tunes model parameter with an association factor that controls average variability of gaussian mixtures and variability of single gaussian mixture per state for more robust modeling. We obtain a re-estimation solution of environmental variables based on the expectation-maximization(EM) algorithm in the cepstral domain. To evaluate the performance of the model compensation methods, we perform experiments on speaker-independent isolated word recognition. Noise sources used are white gaussian and driving car noise. To get corrupted speech we added noise to clean speech at various signal-to-noise ratio(SNR). We use noise mean and variance modeled by 3 frame noise data. Experimental result of the VTS approach is superior to other methods. The scheme of the zero order VTS approach is similar to the modified PMC method in adapting mean vector only. But, the recognition rate of the Zero order VTS approach is higher than PMC and modified PMC method based on log-normal approximation.

• Journal of Korean Society of Rural Planning
• /
• v.20 no.2
• /
• pp.81-90
• /
• 2014

This study was carried out to identify the limitations and problems of organization, as well as present plans to activate the organization through diagnosis on 'My Hometown Keeper' organization that was created for the purpose of growth of agricultural and fishing regions, and environment improvement. Utilizing Weisbord's Six-box Model, an organization diagnosis model useful for diagnosis of 'My Hometown Keeper' organization, 6 areas including organization's objective, structure, relationship, compensation system, leadership, subsidiary device system etc. and 14 survey questions were prepared, and a survey investigation was conducted on the staff at Korea Rural Community Corporation in charge of 'My Hometown Keeper' participating residents and administrative support. Based on the analysis results of survey investigation, the limitations and problems of organization were identified, and as plans to improve these and activate 'My Hometown Keeper' organization, 'Clear establishment of organization's objective and role', 'Preparation of compensation and incentive system', 'Growth of relationship and leadership between constituents' 'Enhancing the utilization of subsidiary device system such as education and information acquisition etc.' etc. were presented.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.405-415
• /
• 2016

This paper presents a model predictive control for shunt active power filters in synchronous reference frame using space vector pulse-width modulation (SVPWM). The three phase load currents are transformed into synchronous rotating reference frame in order to reduce the order of the control system. The proposed current controller calculates reference current command for harmonic current components in synchronous frame. The fundamental load current components are transformed into dc components revealing only the harmonics. The predictive current controller will add robustness and fast compensation to generate commands to the SVPWM which minimizes switching frequency while maintaining fast harmonic compensation. By using the model predictive control, the optimal switching state to be applied to the next sampling time is selected. The filter current contains only the harmonic components, which are the reference compensating currents. In this method the supply current will be equal to the fundamental component of load current and a part of the current at fundamental frequency for losses of the inverter. Mathematical analysis and the feasibility of the suggested approach are verified through simulation results under steady state and transient conditions for non-linear load. The effectiveness of the proposed controller is confirmed through experimental validation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1999.06a
• /
• pp.49-56
• /
• 1999

In this paper, the general formula of disparity estimation based on Bayesian Maximum A Posteriori (MAP) algorithm is derived. The generalized formula is implemented with the plane configuration model and applied to multiple baselined stereograms. The probabilistic plane configuration model consists of independence and similarity among the neighboring disparities in the configuration. The independence probabilistic model reduces the computation and guarantees the discontinuity at the object boundary region. The similarity model preserves the continuity or the high correlation of disparity distribution. In addition, we propose a hierarchical scheme of disparity compensation in the application to multiple-view stereo images. According to the experiments, the derived formula and the proposed estimation algorithm outperformed other ones. The proposed probabilistic models are reasonable and approximate the pure joint probability distribution very well with decreasing the computations to O(n(D)) from O(n(D)4) of the generalized formula. And, the hierarchical scheme of disparity compensation with multiple-view stereos improves the performance without any additional overhead to the decoder.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.12
• /
• pp.2793-2799
• /
• 2013

This paper proposes an effective feature compensation method to improve speech recognition performance in time-varying background noise condition. The proposed method employs principal component analysis to improve the variational model composition method. The proposed method is employed to generate multiple environmental models for the PCGMM-based feature compensation scheme. Experimental results prove that the proposed scheme is more effective at improving speech recognition accuracy in various SNR conditions of background music, compared to the conventional front-end methods. It shows 12.14% of average relative improvement in WER compared to the previous variational model composition method.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2009.06a
• /
• pp.37-38
• /
• 2009