• Structural Engineering and Mechanics
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• v.41 no.1
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• pp.25-41
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• 2012

Kriging surrogate model provides explicit functions to represent the relationships between the inputs and outputs of a linear or nonlinear system, which is a desirable advantage for response estimation and parameter identification in structural design and model updating problem. However, little research has been carried out in applying Kriging model to crack identification. In this work, a scheme for crack identification based on a Kriging surrogate model is proposed. A modified rectangular grid (MRG) is introduced to move some sample points lying on the boundary into the internal design region, which will provide more useful information for the construction of Kriging model. The initial Kriging model is then constructed by samples of varying crack parameters (locations and sizes) and their corresponding modal frequencies. For identifying crack parameters, a robust stochastic particle swarm optimization (SPSO) algorithm is used to find the global optimal solution beyond the constructed Kriging model. To improve the accuracy of surrogate model, the finite element (FE) analysis soft ANSYS is employed to deal with the re-meshing problem during surrogate model updating. Specially, a simple method for crack number identification is proposed by finding the maximum probability factor. Finally, numerical simulations and experimental research are performed to assess the effectiveness and noise immunity of this proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3008-3028
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• 2022

In this paper, we investigate traffic scheduling for a delay-sensitive multi-hop relay network, and aim to minimize the priority-based end-to-end delay of different data packet via joint relay selection, subcarrier assignment, and power allocation. We first derive the priority-based end-to-end delay based on queueing theory, and then propose a two-step method to decompose the original optimization problem into two sub-problems. For the joint subcarrier assignment and power control problem, we utilize an efficient particle swarm optimization method to solve it. For the relay selection problem, we prove its convexity and use the standard Lagrange method to deal with it. The joint relay selection, subcarriers assignment and transmission power allocation problem for each hop can also be solved by an exhaustive search over a finite set defined by the relay sensor set and available subcarrier set. Simulation results show that both the proposed routing scheme and the resource allocation scheme can reduce the average end-to-end delay.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.211-221
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• 2012

The development of wireless sensor networks (WSNs) is progressed slowly due to limited resources, but it is in progress to the development of the latest IP-based IP-WSN by the development of hardware and power management technology. IPv6 over Low power WPAN (6LoWPAN) is capable of IPv6-built low-power devices. In these IP-based WSNs, existing IP-based techniques which was impossible in WSNs becomes possible. 6LoWPAN is based on the IEEE 802.15.4 sensor networks and is a IPv6-supported technology. Host-based mobility management scheme in IP-WSNs are not suitable due to the additional signaling, network-based mobility management scheme is more suitable. In this paper, we propose an enhanced PMIPv6-based route optimization scheme which consider multi-6LoWPAN network environments. All SLMA (Sensor Local Mobility Anchor) of the 6LoWPAN domain are connected with the SPIG (Sensor Proxy Internetworking Gateway) and performs distributed mobility control for the 6LoWPAN-based inter-domain operations. All information of SLMA in 6LoWPAN domain is maintained by SMAG (Sensor Mobile Access Gateway), and then is performed the route optimization quickly. The status information of the route optimization from SPIG is stored to SLMA and it is supported without additional signaling.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8B
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• pp.1105-1114
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• 2010

The Proxy Mobile IPv6 (PMIPv6) has been standardized by the IETF NETLMM WG for network-based mobility management. The PMIPv6 can provide IP mobility for Mobile Nodes (MNs) with low handover latency and less wireless resource usage. But, since the PMIPv6 is basically designed for local mobility management, it cannot support directly global mobility management between different PMIPv6 domains. In the PMIPv6, since all traffic is routed through a Local Mobility Anchor (LMA), it causes a long end-to-end delay and triangular routing problem. Therefore, in this paper, we propose a fast network-based global mobility management scheme and route optimization scheme with a new network entity, called Global Mobility Agent (GMA). Numerical analysis and simulation results show that the proposed scheme is able to support global mobility between different public domains with low handover latency and low end-to-end delay, compared with the PMIPv6.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.166-174
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• 1999

On-line efficiency optimization control of an induction motor drive using neural network is important from the v viewpoints of energy saving and controlling a nonlinear system whose charact81istics are not fully known. This paper p presents a neural networklongleftarrowbased on-line efficiency optimization control for an induction motor drive, which adopts an optimal slip an밍J.lar frequency control. In the proposed scheme, a neuro-controller provides minimal loss operating point i in the whole range of the measured input power. Both simulation and experimental results show that a considerable e energy saving is achieved compared with the conventional constant vlf ratio operation.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.537-542
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• 2001

In recent engineering, the designer has become more and more dependent on computer simulation. But defining exact model using computer simulation is too expensive and time consuming in the complicate systems. Thus, designers often use approximation models, which express the relation between design variables and response variables. These models are called metamodel. In this paper, we introduce one of the metamodel, named Kriging. This model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. This class of interpolating model has flexibility to model response data with multiple local extreme. By reason of this multi modality, we can't use any gradient-based optimization algorithm to find global extreme value of this model. Thus we have to introduce global optimization algorithm. To do this, we introduce DE(Differential Evolution). DE algorithm is developed by Ken Price and Rainer Storn, and it has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. This algorithm is similar to GA(Genetic Algorithm) in populating points, crossing over, and mutating. But it introduces vector concept in populating process. So it is very simple and easy to use. Finally, we show how we determine Kriging metamodel and find global extreme value through two mathematical examples.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.288-300
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• 2006

In this paper, we consider a channel ordering problem that seeks to minimize the total interference in mobile radio networks. If a base station receives connection request from a mobile user, one of the empty channels that are fixed to the base station is assigned to the mobile user. Among several channels available, we can choose one that seems to make least interference with other channels assigned to adjacent base stations. However, a pair of channels that are not separated enough do not generate interference if both of them are not simultaneously used by mobile users. That is, interference between channels may vary depending on the channel assignment sequence for each base station and on the distribution of mobile users. To find a channel assignment sequence that seems to generate minimum interference, we develop an optimization model considering various scenarios of mobile user distribution. Simulation results show that channel assignment sequence determined by the scenario based optimization model significantly reduces the interference provided that scenarios and interference costs are properly generated.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.3
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• pp.219-231
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• 2014

We develop a preliminary design optimization procedure in this paper regarding the wing planform in a solar-powered high-altitude long-endurance unmanned aerial vehicle. A high-aspect-ratio wing has been widely adopted in this type of a vehicle, due to both the high lift-to-drag ratio and lightweight design. In the preliminary design, its characteristics need to be addressed correctly, and analyzed in an appropriate manner. In this paper, we use the three-dimensional Euler equation to analyze the wing aerodynamics. We also use an advanced structural modeling approach based on a geometrically exact one-dimensional beam analysis. Regarding the structural integrity of the wing, we determine detailed configuration parameters, specifically the taper ratio and the span length. Next, we conduct a multi-objective optimization scheme based on the response surface method, using the present baseline configuration. We consider the structural integrity as one of the constraints. We reduce the wing weight by approximately 25.3 % from that in the baseline configuration, and also decrease the power required approximately 3.4 %. We confirm that the optimized wing has sufficient flutter margin and improved static longitudinal/directional stability characteristics, as compared to those of the baseline configuration.

• Structural Engineering and Mechanics
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• v.52 no.1
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• pp.149-172
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• 2014

Four algorithms for damage detection of trusses are presented in this paper. These approaches can detect damage by using both complete and incomplete measurements. The suggested methods are based on the minimization of the difference between the measured and analytical static responses of structures. A non-linear constrained optimization problem is established to estimate the severity and location of damage. To reach the responses, the successive quadratic method is used. Based on the objective function, the stiffness matrix of the truss should be estimated and inverted in the optimization procedure. The differences of the proposed techniques are rooted in the strategy utilized for inverting the stiffness matrix of the damaged structure. Additionally, for separating the probable damaged members, a new formulation is proposed. This scheme is employed prior to the outset of the optimization process. Furthermore, a new tactic is presented to select the appropriate load pattern. To investigate the robustness and efficiency of the authors' method, several numerical tests are performed. Moreover, Monte Carlo simulation is carried out to assess the effect of noisy measurements on the estimated parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.467-473
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• 2007

In this paper, we present a position-based robot hand tracking scheme where a pan-tilt camera is controlled such that a robot hand is always shown in the center of an image frame. We calculate the rotation angles of a pan-tilt camera by transforming the coordinate systems. In order to identify the model parameters, we applied two optimization techniques: a nonlinear least square optimizer and a particle swarm optimizer. From the simulation results, it is shown that the considered parameter identification problem is characterized by a highly multimodal landscape; thus, a global optimization technique such as a particle swarm optimization could be a promising tool to identify the model parameters of a robot hand tracking system, whereas the nonlinear least square optimizer often failed to find an optimal solution even when the initial candidate solutions were selected close to the true optimum.