• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.89-97
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• 2008

Chaotic behavior in motor systems is undesired dynamics in real-time implementation since the speed is oscillated in a wide range and the torque is changed by a random manner. We present an adaptive control approach for time-varying permanent-magnet synchronous motors (PMSM) with chaotic phenomenon. We consider that its parameters are changed randomly within certain bounds. First, a nonlinear system model of a PMSM is transformed to derive a nominal linear control strategy. Then, an auxiliary control for compensating real-time control error occurred by system perturbation due to parameter change is designed by using Lyapunov stability theory. Numerical simulation is accomplished for evaluating its efficiency and reliability comparing with the traditional control method. Additionally, we test our control method in real-time motor experiment including a PSoC based drive system to demonstrate its practical applicability.

• Wind and Structures
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• v.24 no.5
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• pp.481-500
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• 2017

A novel three-degree-of-freedom (DOF) forced vibration system has been developed for identification of aeroelastic (self-excited) load parameters used in time-domain response analysis of wind-excited flexible structures. This system is capable of forcing sinusoidal motions on a section model of a structure that is used in wind tunnel aeroelastic studies along all three degrees of freedom - along-wind, cross-wind, and torsional - simultaneously or in any combination thereof. It utilizes three linear actuators to force vibrations at a consistent frequency but varying amplitudes between the three. This system was designed to identify all the parameters, namely, aeroelastic- damping and stiffness that appear in self-excited (motion-dependent) load formulation either in time-domain (rational functions) or frequency-domain (flutter derivatives). Relatively large displacements (at low frequencies) can be generated by the system, if required. Results from three experiments, airfoil, streamlined bridge deck and a bluff-shaped bridge deck, are presented to demonstrate the functionality and robustness of the system and its applicability to multiple cross-section types. The system will allow routine identification of aeroelastic parameters through wind tunnel tests that can be used to predict response of flexible structures in extreme and transient wind conditions.

• Computers and Concrete
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• v.20 no.4
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• pp.369-380
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• 2017

The effects of the vertical component of a ground motion on the earthquake performances of semi-ductile high-rise R/C structures were investigated in the present study. Linear and non-linear time-history analyses were conducted on an existing in-service R/C building for the loading scenarios including and excluding the vertical component of the ground motion. The ratio of the vertical peak acceleration to the horizontal peak acceleration (V/H) of the ground motion was adopted as the main parameter of the study. Three different near-source earthquake records with varying V/H ratio were used in the analyses. The linear time-history analyses indicated that the incorporation of the vertical component of a ground motion into analyses greatly influences the vertical deflections of a structure and the overturning moments at its base. The lateral deflections, the angles of rotation and the base shear forces were influenced to a lesser extent. Considering the key indicators of vertical deflection and overturning moments determined from the linear time-history analysis, the non-linear analyses revealed that the changes in the forces and deformations of the structure with the inclusion of the vertical ground motion are resisted by the shear-walls. The performances and damage states of the beams were not affected by the vertical ground motion. The vertical ground motion component of earthquakes is markedly concluded to be considered for design and damage estimation of the vertical load-bearing elements of the shear-walls and columns.

• Earthquakes and Structures
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• v.3 no.1
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• pp.59-81
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• 2012

A ductility inverse-mapping method for SDOF systems including passive dampers is proposed which enables one to find the maximum acceleration of ground motion for the prescribed maximum response deformation. In the conventional capacity spectrum method, the maximum response deformation is computed through iterative procedures for the prescribed maximum acceleration of ground motion. This is because the equivalent linear model for response evaluation is described in terms of unknown maximum deformation. While successive calculations are needed, no numerically unstable iterative procedure is required in the proposed method. This ductility inverse-mapping method is applied to an SDOF model of bilinear hysteresis. The SDOF models without and with passive dampers (viscous, viscoelastic and hysteretic dampers) are taken into account to investigate the effectiveness of passive dampers for seismic retrofitting of building structures. Since the maximum response deformation is the principal parameter and specified sequentially, the proposed ductility inverse-mapping method is suitable for the implementation of the performance-based design.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1905-1910
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• 2003

It is well known that parameter uncertainties and time-delays cannot be avoided in practice and result in poor performance and even instability. Nevertheless, to the authors' best knowledge, there exist few results on model predictive control (MPC) handling explicitly uncertain time-delayed systems. In this paper, we present an MPC algorithm for uncertain time-varying systems with input constraints and state-delay. An optimization problem is suggested to find a memoryless state-feedback MPC law and the closed-loop stability is established under feasibility and certain conditions.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.02a
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• pp.36-47
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• 1999

Terzaghi's theory of one-dimensional consolidation is restricted in its applicability to relatively thin layers and small incremental loading. Because it is assumed to infinitesimal strain and linear material function. For this reason, Gibson et al established a rigorous formulation for the one-dimensional nonlinear finite strain consolidation theory. There are some difficulties in the application of finite strain consolidation theory. The developed program consisted of several forms and modules. These forms and modules with graphic-user-interfaced format are used in analysis of consolidation practices. For the purpose of verification of developed program. the results of case study and prediction of developed program are compared. The results of comparison is fairly well with prediction and measured data. And with varying finite strain consolidation parameter, g(e) or λ(e), the sensitivity of predicted values were examined.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.308-313
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• 2018

In this paper, we propose a sampled-data model predictive tracking control deign for leader-following control of multi-mobile robot system. The error dynamics of leader-following robots is modeled as a Linear Parameter Varying (LPV) model. Also, the Lyapunov function is presented to guarantee stability of the networked control system. Based on the stabilization condition using a quadratic Lyapunov function approach, model predictive sampled-data controller is designed. Finally, the leader-following control of multi mobile robots is simulated to show effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1871-1876
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• 2005

In this paper, We present a new nonlinear adaptive control law using a disturbance accommodating control (DAC) observer for a Japanese automatic landing flight experiment vehicle called ALFLEX. A future spaceplane must have ability to deal with greater fluctuations in the stability and control derivatives of flight dynamics, because its flight region is much wider than that of conventional aircraft. In our previous studies, digital adaptive flight control systems have been developed based on a linear-parameter-varying (LPV) model depending on dynamic pressure, and obtained good simulation results. However, under previous control laws, it is difficult to accommodate uncertainties represented by disturbance and nonlinearity, and to design a stable flight control system. Therefore, in this study, we attempted to design a nonlinear adaptive control law using the DAC Observer and inverse dynamic methods. A good tracking property of the obtained system was confirmed in numerical simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.314-320
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• 2012

This paper proposes a new robust motion deblurring filter using the inertial sensor measurements for strapdown image IR applications. With taking the PSF measurement error into account, the motion blurred image is modeled by the linear uncertain state space equation with the noise corrupted measurement matrix and the stochastic parameter uncertainty. This motivates us to solve the motion deblurring problem based on the recently developed robust least squares estimation theory. In order to suppress the ringing effect on the deblurred image, the robust least squares estimator is slightly modified by adoping the ridge-regression concept. Through the computer simulations using the actual IR scenes, it is demonstrated that the proposed algorithm shows superior and reliable motion deblurring performance even in the presence of time-varying motion artifact.