• Physical Therapy Korea
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• v.14 no.2
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• pp.1-10
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• 2007

The purpose of this experiment was to investigate the applicability of audio-visual modeling for improving the efficiency of rehabilitative programs by analyzing the effects of observing these various models on the capacity of stroke patients to perform upper limb activities. Twenty-one stroke patients participated in the experiment and were randomly assigned to either task modeling, sport modeling, or control group. During 2 weeks of intervention, subjects in all groups participated in the physical practice of experimental tasks. These tasks comprised of a Nine Hole Peg Test, the Jebsen-Taylor Hand Function tests, and locomotion. These tasks were performed 5 days a week, 30 min per day. In addition to the physical practice, the task modeling group observed a model performing experimental tasks and locomotive activities for 20 min, while the sport modeling group observed a model performing various sport activities for 20 min. Subjects' ability to perform the experimental tasks was measured 3 times, before, immediately after, and 1 week after the intervention. Analyses of the capacity to perform upper extremity activities displayed significant improvement from the pre-test to immediate and delayed post-tests in all groups. However, the amount of improvement was the highest in the task modeling group. The task modeling group was superior to the control group in the post-test of all experimental tasks, whereas the sport modeling group did not display significant differences from the control group. These results suggest that audio-visual modeling can be used as an effective cognitive intervention for facilitating the rehabilitation of stroke patients, and its rehabilitative effect can be maximized when the program is comprised of performance scenes directly related to the target task.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.6-93
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• 2001

This paper describes the results on the fuzzy control in the modeling equipment of the height-level of water, in comparison with the results of PID control in the same system. By using two types of the fuzzy control, it is reported that the response rapidity, smoothness and complexity of the fuzzy control are superior to PID control by the experiment results.

• Journal of KSNVE
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• v.11 no.2
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• pp.292-300
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• 2001

This research is concerned with the validation of the modeling technique and controller design for slewing beam structures. When cantilever beam rotates about axes perpendicular to the undeformed beam's longitudinal axis, it experiences inertial loading. Hence, the beam vibrates from the initial stage of slewing. In this paper, the analytical model for a single slewing flexible beam with surface bonded piezoelectric sensor and actuator is developed using the Hamilton's principle with discretization by the assumed mode method. Comparisons with the theoretical model are made based upon the frequency responses and time responses. A new factor called the coupling coefficient is introduced to incorporate the discrepancies between the theoretical and experimental results. The slewing is achieved by applying the PID control, which is found to be less sensitive to vibrations. The vibrations are controlled by PPF controller, which is found to be effective in suppressing residual vibrations after slewing. The vibrations occurred during slewing is difficult to control because the piezoceramic actuator is not powerful enough to overcome inertial loadings.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.54-61
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• 2008

This paper presents a method for reducing modelling error in the linear motion system with voicecoil actuator (VCA). A model of linear motion system composed of a mechanism and control was prepared to verify the proposed method. In modeling of the system, the damping coefficient obtained experimentally is applied to the model in order to consider the effect of the viscous friction for the moving part in VCA. The response velocity of VCA for duty ratio of PWM signal was analyzed in the time domain. Consequently, the relation between velocity and duty ratio was obtained. The result from the experiment showed an error of 9% when compared with that of simulation. In order to reduce the modeling error, impedance variation according to input frequency was analyzed, and equivalent impedance with multi-frequency was applied to the control part. As a result, the modeling error decreased to 5%.

• The Journal of the Acoustical Society of Korea
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• v.22 no.1E
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• pp.33-42
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• 2003

Kuo et al proposed an on-line method for an adaptive prediction error filter for improving secondary path modeling performance in the modeling method of the secondary path. This method have some disadvantages, namely having to use additive noise with the result that noise control performance is not good since it is focused on the estimated performance of the secondary path. In this paper, we proposes a modified Kuo model using gain control parameter and delay. It uses a reference signal for additive noise to improve the problems in the existing Kuo model.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.86-100
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• 2008

Most of the previously employed dynamic modeling approaches, including Natural Orthogonal Complement Algorithm, have limitations on their application to the mobile robot, specifically at singular configurations. Also, in their dynamic modeling of mobile robots, wheel dynamics is usually ignored assuming that its dynamic effect is negligibly small. As a remedy for this, a singularity-free operational space dynamic modeling approach based on Lagrange's form of the D' Alembert principle is proposed, and the singularity-free characteristic of the proposed dynamic modeling is discussed in the process of analytical derivation of the proposed dynamic model. Then an accurate dynamic model taking into account the wheel dynamics of the omni-directional mobile robot is derived, and through simulation it is manifested that the effect of the wheel dynamics on the whole dynamic model of the mobile robot may not be negligible, but rather in some cases it is significantly large, possibly affecting the operational performances of dynamic model-based control algorithms. Lastly, the importance of its accurate dynamic model is further illustrated through impulse analysis and its simulation for the mobile robot.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.4
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• pp.542-548
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• 2012

This study presents a new method of system modeling by using the Discrete Fourier Transform for the position control system of DC Motor. And the proposed method is similar to the method of System Identification by analysis of correlation of the measured input-output data. The measured output signals are transformed to the frequency domain using DFT. The Fourier Spectrum of the transformed signals is used for knowing to the feature of having an important effect on the system. And transfer function of the second order system is estimated by the dominant parameter which is computed in the magnitude and the phase of Fourier spectrum of the transformed signals. In addition, the output signal includes the unique feature of system. So, although the basic parameter of the system is unknown for us, the proposed method has an advantage to system modeling. And the controller is easily designed by the estimated transfer function. Thus, in this paper, the proposed method is applied to the system modeling for the position control system of DC Motor and the PD-controller is designed by the estimated model. And the efficiency and the reliability of the proposed method are verified by the experimental result.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.577-582
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• 2002

Neural network can be trained to approximate an arbitrary nonlinear function of multivariate data like the mini-mill crown values in Automatic Shape Control. The trained weights of neural network can evaluate or generalize the process data outside the training vectors. Sometimes, the blind modeling of the process data is necessary to compare with the scattered analytical model of mini-mill process in isolated electro-mechanical forms. To come up with a viable model, we propose the blind neural-based range-division domain-clustering piecewise-linear modeling scheme. The basic ideas are: 1) dividing the range of target data, 2) clustering the corresponding input space vectors, 3)training the neural network with clustered prototypes to smooth out the convergence and 4) solving the resulting matrix equations with a pseudo-inverse to alleviate the ill-conditioning problem. The simulation results support the effectiveness of the proposed scheme and it opens a new way to the data analysis technique. By the comparison with the statistical regression, it is evident that the proposed scheme obtains better modeling error uniformity and reduces the magnitudes of errors considerably. Approximatly 10-fold better performance results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1292-1295
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• 1996

This paper proposes an adaptive control technique for the autopilot design of STT missile. Dynamics of the missile is highly nonlinear and the equilibrium point is vulnerable to change due to fast maneuvering. Therefore nonlinear control techniques are desirable for the autopilot design of the missile. The nonlinear controller requires the exact model to obtain satisfactory performance. Generally a look-up table is used for the dynamic coefficients of a missile, so there must be coefficients error during actual flight, and the performance of the nonlinear controller using these data can be degraded. The proposed adaptive control technique compensates the nonlinear controller with modeling error resulting from the error of aerodynamic data and disturbance. To investigate the usefulness, the proposed method is applied to autopilot design of STT missile through simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.349-352
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• 1997

A Piezoelectric actuator yields hysteresis effect due to its composed ferroelectric. Hysteresis nonlinearity is neglected when a piezoelectric actuator moves with short stroke. However when it moves with long stroke and high frequency, the hysteresis nonlinearity can not be neglected. The hysteresis nonlinearity of piezoelectric actuator degrades the control performance in precision position control. In this paper, in order to improve the control performance of piezoelectric actuator, an inverse modeling scheme is proposed to compensate the hysteresis nonlinearity problem. And feedforward-feedforward-feedback controller is proposed to give a good tracking performance. The Feedforward controller is inverse hysteresis model, and PID control is sued as a feedback controller. To show the feasibility of the proposed controller and hysteresis modeling, some experiments have been carried out. It is concluded hat the proposed control scheme gives good tracking performance.