• Steel and Composite Structures
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• v.8 no.5
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• pp.343-359
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• 2008

In the present study, an efficient method for the optimum design of three-dimensional (3D) steel framed structures is proposed. In this method, in addition to choosing the best position of columns based on architectural requirements, the optimum cross-sectional dimensions of elements are determined. The preliminary design variables are considered as the number of columns in structural plan, which are determined by a direct optimization method suitable for discrete variables, without requiring the evaluation of derivatives. After forming the geometry of structure, the main variables of the cross-sectional dimensions are evaluated, which satisfy the design constraints and also achieve the least-weight of the structure. To reduce the number of finite element analyses and the overall computational time, a new third order approximate function is introduced which employs only the diagonal elements of the higher order derivatives matrices. This function produces a high quality approximation and also, a robust optimization process. The main feature of the proposed techniques that the higher order derivatives are established by the first order exact derivatives. Several examples are solved and efficiency of the new approximation method and also, the proposed method for the best position of columns in 3D steel framed structures is discussed.

• 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.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.17-27
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• 2007

Minimum-time attitude maneuvers of three-axis stabilized spacecraft are presented to study the feasibility of using three magnetic torquers perform large angle maneuvers. Previous applications of magnetic torquers have been limited to spin-stabilized satellites or supplemental actuators of three axis stabilized satellites because of the capability of magnetic torquers to produce torques about a specific axes. The minimum-time attitude maneuver problem is solved by applying a parameter optimization method for orbital cases to verify that the magnetic torque system can perform as required. Direct collocation and a nonlinear programming method with a constraining method by Simpson's rule are used to convert the minimum-time maneuver problems into parameter optimization problems. An appropriate number of nodes is presented to find a bang-bang type solution to the minimum-time problem. Some modifications in the boundary conditions of final attitude are made to solve the problem more robustly and efficiently. The numerical studies illustrate that the presented method can provide a capable and robust attitude reorientation by using only magnetic torquers. However, the required maneuver times are relatively longer than when thrusters or wheels are used. Performance of the system in the presence of errors in the magnetometer as well as the geomagnetic field model still good.

• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.463-470
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• 2010

We presented a very fast and robust method of text line segmentation based on the DCT blocks of color image without decompression and binary transformation processes. Using DC and another three primary AC coefficients from block DCT we created a gray-scale image having reduced size by 8x8. In order to detect and locate white strips between text lines we analyzed horizontal and vertical projection profiles of the image and we applied a direct markov model to recover the missing white strips by estimating hidden periodicity. We presented performance results. The results showed that our method was 40 - 100 times faster than traditional method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.517-522
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• 2019

This paper proposes a new motor parameter estimation method. Because the proposed method is based on difference equations, it does not affect the error in the voltage magnitude so called dead-time effect. Information on the motor constant may be needed to improve the motor control performance. For example, a control technique called DTC (Direct Torque Control) requires a motor constant when calculating the torque and flux magnitude. As another example, in the case of predictive control, information on the motor parameters is required to generate voltage references. Because the constant of the motor fluctuates according to the driving environment, it is essential to estimate the correct motor constant because the control performance is degraded when incorrect motor information is used. In the proposed scheme, the motor constant estimated based on the voltage difference equation is obtained using the RLS (Recursive Least Square) technique. The RLS algorithm is applied to obtain the value through an iterative calculation so that the estimation performance is robust to noise. The simulation results carried out with surface mounted permanent magnet motors confirmed the validity of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.3
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• pp.261-269
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• 2014

This paper provides an overview of the basics and recent studies of Lyapunov-based nonlinear adaptive control, the aim of which is to improve or maintain the performance and stability of the closed-loop system by cancelling out the presumable uncertainties in the nonlinear system dynamics. The design principles are essentially based on Lyapunov's direct method. In this survey, we provide a comprehensive overview of Lyapunov-based nonlinear adaptive control techniques with simplified effective design examples, which are to be elaborated as related recent results are gradually shown. The scope of the survey contains research on singularity problems in adaptive control, the techniques to deal with linearly and nonlinearly parameterized uncertainties, robust neuro-adaptive control, and adaptive control methodologies combined with various nonlinear control techniques such as sliding-mode control, back-stepping, dynamic surface control, and optimal/$H_{\infty}$ control.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2540-2545
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• 2003

We propose a new technique to the design and real-time implementation of an adaptive controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot consisting of two 4-d.o.f. robots at the joint space and cartesian space.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.3
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• pp.108-111
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• 2002

This paper proposes an new water mark embedding and extraction technique which extends the direct sequence spread spectrum technique. The proposed technique approximates the complexity of image and block in spatial domain using Laplacian filtering and watermark is adaptively embedded in the mid-frequency DCT components. Local parity bits are attached to higher-frequency DCT components and they are used to detect extraction errors and correct those errors. In extraction process the proposed method boosts the higher frequency components of image and extracts the watermark by demodulation and this information is verified and adjusted by parity bits. Experimental results show it is invisible and robust to several external attacks.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.826-832
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• 2016

A two-wheeled balancing mobile robot (TWBMR) has the characteristics of both nonlinear and underactuated system. In this paper, the disturbances acting on a TWBMR are classified into body disturbance and wheel disturbance. Additionally, we describe a nonlinear disturbance observer, which is suitable as a single input multi-output (SIMO) system for the longitudinal motion of TWBMR. Finally, we propose a reasonable disturbance compensation technique that combines the indirect reference input of equilibrium point and the direct torque compensation input. Simulations and experimental results show that the proposed disturbance compensation method is an effective way to achieve robust postural stability, specifically on inclined terrains.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.157-163
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• 2005

In this paper, we present the multimodal system based on the fusion of two user-friendly biometric modalities: Iris and Face. In order to reach robust identification and verification we are going to combine two different biometric features. we specifically apply 2-D discrete wavelet transform to extract the feature sets of low dimensionality from iris and face. And then to obtain Reduced Joint Feature Vector(RJFV) from these feature sets, Direct Linear Discriminant Analysis (DLDA) is used in our multimodal system. In addition, the Synergetic Neural Network(SNN) is used to obtain matching score of the preprocessed data. This system can operate in two modes: to identify a particular person or to verify a person's claimed identity. Our results for both cases show that the proposed method leads to a reliable person authentication system.