• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.442-445
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• 1991

In the physical system, if we can precisely control an acceleration and force, we can improve the performance of their integral values, velocity and position. From this point of view, in this paper we try to use an obverser which is constructed by using Variable Structure System for estimating the acceleration in the system with the bounded unknown disturbance and the parameter mismatching. To obtain the robust control performance, the VSS with sliding mode is adopted in the design of the servo controller.

• Earthquakes and Structures
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• v.7 no.3
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• pp.365-384
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• 2014

The intensity of a ground motion can be measured by a number of parameters, some of which might exhibit robust correlations with the damage of structures subjected to that motion. In this study, 204 near-fault pulse-type records are selected and their seismic parameters are determined. Time history and damage analyses of a tested 3-storey reinforced concrete frame representing for low-rise reinforced concrete buildings subjected to those earthquake motions are performed after calibration and comparison with the available experimental results. The aim of this paper is to determine amongst several available seismic parameters, the ones that have strong correlations with the structural damage measured by a damage index and the maximum inter-story drift. The results show that Velocity Spectrum Intensity is the leading parameter demonstrating the best correlation, followed by Housner Intensity, Spectral Acceleration and Spectral Displacement. These seismic parameters are recommended as reliable parameters of near-fault pulse-type motions related to damage potential of low-rise reinforced concrete structures. The results also reaffirm that the conventional and widely used parameter of Peak Ground Acceleration does not exhibit a good correlation with the structural damage.

• Earthquakes and Structures
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• v.21 no.6
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• pp.627-639
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• 2021

Fragility curves are being more significant as a useful tool for evaluating the relationship between the earthquake intensity measure and the effects of the engineering demand parameter on the buildings. In this paper, the effect of different site conditions on the vulnerability of the structures was examined through the fragility curves taking into account different strength capacities of the precast columns. Thus, typical existing single-story precast RC industrial buildings which were built in Turkey after the year 2000 were examined. The fragility curves for the three typical existing industrial structures were derived from an analytical approach by performing non-linear dynamic analyses considering three different soil conditions. The Park and Ang damage index was used in order to determine the damage level of the members. The spectral acceleration (Sa) was used as the ground motion parameter in the fragility curves. The results indicate that the fragility curves were derived for the structures vary depending on the site conditions. The damage probability of exceedance values increased from stiff site to soft site for any Sa value. This difference increases in long period in examined buildings. In addition, earthquake demand values were calculated by considering the buildings and site conditions, and the effect of the site class on the building damage was evaluated by considering the Mean Damage Ratio parameter (MDR). Achieving fragility curves and MDR curves as a function of spectral acceleration enables a quick and practical risk assessment in existing buildings.

• Earthquakes and Structures
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• v.22 no.1
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• pp.53-64
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• 2022

This study proposes an intelligent semi-active isolation system combining a variable-stiffness control device and ground motion characteristic prediction. To determine the optimal control parameter in real-time, a genetic algorithm (GA)-fuzzy control law was developed in this study. Data on various types of ground motions were collected, and the ground motion characteristics were quantified to derive a near-fault (NF) characteristic ratio by employing an on-site earthquake early warning system. On the basis of the peak ground acceleration (PGA) and the derived NF ratio, a fuzzy inference system (FIS) was developed. The control parameters were optimized using a GA. To support continuity under near-fault and far-field ground motions, the optimal control parameter was linked with the predicted PGA and NF ratio through the FIS. The GA-fuzzy law was then compared with other control laws to verify its effectiveness. The results revealed that the GA-fuzzy control law could reliably predict different ground motion characteristics for real-time control because of the high sensitivity of its control parameter to the ground motion characteristics. Even under near-fault and far-field ground motions, the GA-fuzzy control law outperformed the FPEEA control law in terms of controlling the isolation layer displacement and the superstructure acceleration.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.208-214
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• 2014

Vehicle dynamic states used in various advanced driving safety systems are influenced by road geometry. Among the road geometry information, the vehicle pitch angle influenced by road slope and acceleration-deceleration is essential parameter used in pose estimation including the navigation system, advanced adaptive cruise control and others on sag road. Although the road slope data is essential parameter, the method measuring the parameter is not commercialized. The digital map including the road geometry data and high-precision DGPS system such as DGPS(Differential Global Positioning System) based RTK(Real-Time Kinematics) are used unusually. In this paper, low-cost cascade extended Kalman filter(CEKF) based road slope estimation method is proposed. It use cascade two EKFs. The EKFs use several measured vehicle states such as yaw rate, longitudinal acceleration, lateral acceleration and wheel speed of the rear tires and 3 D.O.F(Degree Of Freedom) vehicle dynamics model. The performance of proposed estimation algorithm is evaluated by simulation based on Carsim dynamics tool and T-car based experiment.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.6
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• pp.523-529
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• 2013

A sensorless speed control of a permanent magnet synchronous motor(PMSM) which utilizes MRAS based scheme to estimate rotor speed and position is presented. Considering an error between real and estimated rotor position values, a state equation of PMSM in the synchronous d-q reference frame is represented. A state equation of model system which uses estimated speed and nominal parameter values is expressed. To minimize the errors between the derivatives of d-q axis currents of real and model system, MRAS based adaptation mechanisms for the estimation of rotor speed and position are derived. On the other hand, for the acceleration stage of motor just before the sensorless operation, an acceleration scheme using only d-axis current control is proposed. To show the validity of the proposed scheme, experimental works are carried out and evaluated. During acceleration stage, the acceleration scheme using only d-axis current command shows good acceleration performance and controlled current level. For the sensorless operation, at low speed (5% of rated speed), a good performance is observed.

• Wind and Structures
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• v.30 no.3
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• pp.275-288
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• 2020

High-rise buildings are very slender and flexible. Their low stiffness values make them vulnerable to horizontal loads, such as those associated with wind or earthquakes. For high-rise buildings, the threat to serviceability caused by wind-induced vibration is an important problem. To estimate the serviceability under wind action, the response acceleration of a building at the roof height is used. The response acceleration is estimated by the same wind speed at all wind directions. In general, the effect of wind direction is not considered. Therefore, the response accelerations obtained are conservative. If buildings have typical plans and strong winds blow from relatively constant wind directions, it is necessary to account for the wind direction to estimate the response accelerations. This paper presents three methods of evaluating the response accelerations while considering the effects of wind direction. These three serviceability evaluation methods were estimated by combining the wind directional frequency data obtained from a weather station with the results of a response analysis using wind tunnel tests. Finally, the decrease in the efficiencies of the response acceleration for each serviceability evaluation method was investigated by comparing the response acceleration for the three methods accounting for wind direction with the response acceleration in which wind direction was not considered.

• Smart Structures and Systems
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• v.29 no.4
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• pp.599-616
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• 2022

Bridge displacement contains vital information for bridge condition and performance. Due to the limits of direct displacement measurement methods, the indirect displacement reconstruction methods based on the strain or acceleration data are also developed in engineering applications. There are still some deficiencies of the displacement reconstruction methods based on strain or acceleration in practice. This paper proposed a novel method based on long short-term memory (LSTM) networks to reconstruct the bridge dynamic displacements with the strain and acceleration data source. The LSTM networks with three hidden layers are utilized to map the relationships between the measured responses and the bridge displacement. To achieve the data fusion, the input strain and acceleration data need to be preprocessed by normalization and then the corresponding dynamic displacement responses can be reconstructed by the LSTM networks. In the numerical simulation, the errors of the displacement reconstruction are below 9% for different load cases, and the proposed method is robust when the input strain and acceleration data contains additive noise. The hyper-parameter effect is analyzed and the displacement reconstruction accuracies of different machine learning methods are compared. For experimental verification, the errors are below 6% for the simply supported beam and continuous beam cases. Both the numerical and experimental results indicate that the proposed data fusion method can accurately reconstruct the displacement.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.421-424
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• 1990

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic systems is presented. In the learning control structure, tracking and feedforward input converge globally and asymptotically as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of length of trajectories, it may be achieved with only system trajectories of small duration. In addition, these learning control schemes are expected to be effectively applicable to time-varying parametric systems as well as time-invariant systems, for the parameter estimation is performed at each fixed time along the iteration. Finally, no usage of acceleration signal and no in version of estimated inertia matrix in the parameter estimator makes these learning control schemes more feasible.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.427-438
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• 1991

An iterative learning control scheme for exact-tracking control and parameter estimation of uncertain robotic system is preented. In the learning control structure, the control input converges globally and asymtotically to the desired input as iteration increases. Since convergence of parameter errors depends only on the persistent exciting condition of system trajectories along the iteration independently of the time-duration of trajectories, it may be achieved with system trajectories with small duration. In addition, the proposd learning control schemes are applicable to time-varying parametric systems as well as time-invariant systems, because the parameter estimation is performed at each fixed time along the iteration. In the parameter estimator, the acceleration information as well as the inversion of estimated inertia matrix are not used at all, which makes the proposed learning control schemes more feasible.