• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.52-55
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• 1997

In this paper, the case study of reducing rotational errors is done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. For the most case, the electrical runout of sensor target is big even in well-finished surface; this runout can cause a rotation error amplified by feedback control system. The adaptive feedforward method based on LMS algorithm is discussed to compensate this kind of runout effects, and investigated its effectiveness by numerical simulation and experimental analysis. The rotor orbit size in both bearings is reduced about to 5 pin due to lX rejection by feedforward control up to 50, 000 rpm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.1011-1015
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• 2000

In this paper, the case studies of reducing rotational errors is theoretically done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. The adaptive feedforward method based on LMS algorithm is discussed to compensate output and input disturbances, and investigated its effectiveness by numerical simulation. The feedforward control reduced external excitation and rotational error for specified frequency. The interpolation method using impulse function for cancelling the electrical 'uncut is studied. These methods show their effectiveness for the rotational accuracy of the improving magnetic bearing spindle through some simulation results of the rotational error decreased by them.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.997-1001
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• 2000

In this paper, the case studies of reducing rotational errors is theoretically done for a grinding spindle with an active magnetic bearing system. The rotational errors acting on the magnetic bearing spindle are due to mass unbalance of rotor, runout, grinding excitation and unmodeled nonlinear dynamics of electromagnets. For the most case, the electrical runout of sensor target is big even in well finished surface, this runout can cause a rotation error amplified by feedback control system. The adaptiveed forward method based on LMS algorithm is discussed to compensate this kind of runout effects, and investigated its effectiveness by numerical simulation and experimental analysis. The electrical runout form the rear sensor target of grind spindle is about 70$\mu\textrm{m}$ with harmonic frequencies. The rotor orbit size in rear bearing is reduced about to 5$\mu\textrm{m}$ due to 1X and 2X rejection by feedforward control.

• Smart Structures and Systems
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• v.14 no.3
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• pp.327-345
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• 2014

This paper presents a composite control strategy for the active suppression of vibration due to the unknown disturbances, such as external excitation, harmonic effects and control spillover, as well as high-frequency accelerometer measurement noise in the all-clamped stiffened plate. The proposed composite control action based on the modal approach, consists of two contributions including feedback part and feedforward part. The feedback part is the well-known PID controller, which is widely used to increase the structure damping and improve its dynamic performance close to the resonance frequencies. In order to get better performance for vibration suppression, the weight matrixes is optimized by chaos sequence. Then an improved disturbance observer (IDOB) as the feedforward compensation part is developed to enhance the vibration suppression performance of PID under various disturbances and uncertainties. The proposed IDOB can simultaneously estimate the various disturbances dynamically as well as measurement noise acting on the system and suppress them by feedforward compensation design. A rigorous analysis is also given to show why the IDOB can effectively suppress the unknown disturbances and measurement noise. In order to verify the proposed composite control algorithm (IDOB-PID), the dSPACE real-time simulation platform is used and an experimental platform for the all-clamped stiffened plate active vibration control system is set up. The experimental results demonstrate the effectiveness, practicality and strong anti-disturbances ability of the proposed control strategy.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.18-25
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• 1997

The feedforward control algorithm for active noise control exhibits high stability and performance robustness. But it has a slow convergence speed and requires a correlated reference signal. Broadband active control systems typically use feedback control in order to increase the convergence speed and to avoid the problems associated with obtaining and decoupling a suitable reference signal. However, it is well known that conventional feedback control systems have a gain-bandwidth limitation and stability problem. This paper presents the new system based on the combination of both feedforward and feedback system in order to increase the convergence speed. The proposed system uses a proposed control algorithm termed "optional-summed" algorithm in which the "optional summed reference signal" comprised of weighted sum of an original reference signal and a eror signal, is used as an input to an adaptive system. Thus, the proposed system can have faster convergence speed and better performance than either feedforward or feedback system using the Filtered-x LMS algorithm as almost equivalent complexity of computation as it. Several simulation results demonstrating the good properties of the proposed adaptive system as well as verifying the analytical results are also presented in the paper.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1194-1198
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• 1993

Active roll control can improve handling and ride comfort. Dynamic characteristics of the hydraulic actuators for active suspension, which can be modeled as the 1'st order time lag system, hinders the performance improvement. To overcome this shortcoming a predictive controller is designed based on 3 d.o.f. linear vehicle handling model. The effect of this controller is studied through the simulation based on 10 d.o.f. nonlinear vehicle model and the results is compared to that of feedforward controller which uses lateral acceleration as control signal.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.3
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• pp.191-198
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• 2015

Noise propagated through the ventilation openings of enclosures is actively controlled using an FIR filter. The enclosures considered in this paper are used for isolating noise due to machinery. This method is of limited use because of the ventilation openings through which most of noise is propagated. Feedforward control strategy is incorporated to minimize the acoustic power propagated through the openings. For the real-time implementation, although it is numerical study, the controller is implemented using an FIR filter. The acoustic transfer functions of the pressure on the openings of the enclosure to the primary source and to the secondary source are numerically calculated using the boundary element method. The performance analysis of the active control is conducted with the time-domain simulation using Matlab Simulink.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2495-2497
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• 2004

A system, featuring the hybrid isolator for control in the vertical direction, of active microvibration control was proposed. The main components of this system are a stage vibration isolation table with built-in acceleration sensors for detecting microvibration, hybrid isolators and a digital controller with high precision signal converters. The vibration control algorithm is focused on settling-time critical application and feedback/feedforward combination.

• International Journal of Contents
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• v.7 no.1
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• pp.14-22
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• 2011

Temporal Sign Language Recognition (TSLR) from hand motion is an active area of gesture recognition research in facilitating efficient communication with deaf people. TSLR systems consist of two stages: a motion sensing step which extracts useful features from signers' motion and a classification process which classifies these features as a performed sign. This work focuses on two of the research problems, namely unknown time varying signal of sign languages in feature extraction stage and computing complexity and time consumption in classification stage due to a very large sign sequences database. In this paper, we propose a combination of Dynamic Time Warping (DTW) and application of the Single hidden Layer Feedforward Neural networks (SLFNs) trained by Extreme Learning Machine (ELM) to cope the limitations. DTW has several advantages over other approaches in that it can align the length of the time series data to a same prior size, while ELM is a useful technique for classifying these warped features. Our experiment demonstrates the efficiency of the proposed method with the recognition accuracy up to 98.67%. The proposed approach can be generalized to more detailed measurements so as to recognize hand gestures, body motion and facial expression.