• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.881-886
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.138-143
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• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.

• Industrial Engineering and Management Systems
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• v.7 no.2
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• pp.171-181
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• 2008

Home care, known also as domiciliary care, is part of the community care service that is a responsibility of the local government authorities in the UK as well as many other countries around the world. The aim is to provide the care and support needed to assist people, particularly older people, people with physical or learning disabilities and people who need assistance due to illness to live as independently as possible in their own homes. It is performed primarily by care workers visiting clients' homes where they provide help with daily activities. This paper is concerned with the dispatching of care workers to clients in an efficient manner. The optimized routine for each care worker determines a schedule to achieve the minimum total cost (in terms of distance traveled) without violating the capacity and time window constraints. A collaborative population-based meta-heuristic called Particle Swarm Optimization (PSO) is applied to solve the problem. A particle is defined as a multi-dimensional point in space which represents the corresponding schedule for care workers and their clients. Each dimension of a particle represents a care activity and the corresponding, allocated care worker. The continuous position value of each dimension determines the care worker to be assigned and also the assignment priority. A heuristic assignment scheme is specially designed to transform the continuous position value to the discrete job schedule. This job schedule represents the potential feasible solution to the problem. The Earliest Start Time Priority with Minimum Distance Assignment (ESTPMDA) technique is developed for generating an initial solution which guides the search direction of the particle. Local improvement procedures (LIP), insertion and swap, are embedded in the PSO algorithm in order to further improve the quality of the solution. The proposed methodology is implemented, tested, and compared with existing solutions for some 'real' problem instances.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.931-938
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• 2008

In this paper, a novel localization algorithm robust to the unmodeled systematic odometry errors is proposed for low-cost non-holonomic mobile robots. It is well known that the most pose estimators using odometry measurements cannot avoid the performance degradation due to the dead-reckoning of systematic odometry errors. As a remedy for this problem, we tty to reflect the wheelbase error in the robot motion model as a parametric uncertainty. Applying the Krein space estimation theory for the discrete-time uncertain nonlinear motion model results in the extended robust Kalman filter. This idea comes from the fact that systematic odometry errors might be regarded as the parametric uncertainties satisfying the sum quadratic constrains (SQCs). The advantage of the proposed methodology is that it has the same recursive structure as the conventional extended Kalman filter, which makes our scheme suitable for real-time applications. Moreover, it guarantees the satisfactoty localization performance even in the presence of wheelbase uncertainty which is hard to model or estimate but often arises from real driving environments. The computer simulations will be given to demonstrate the robustness of the suggested localization algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.76-84
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• 2009

Since too much information has been generated, it became very difficult to find out valuable and necessary information. In order to deal with the problem of information overload, the taxonomy for information visualization techniques has been based upon visualized shapes such as tree map, fisheye view and parallel coordinates, so that it was difficult to choose the right representation technique by data characteristics. Therefore, this study was designed to introduce a new taxonomy for the information visualization by data characteristics which defined by space (3D vs. multi-dimensions), time (continuous vs. discrete), and relations of data (qualitative vs. quantitative). To verify the new taxonomy, forensic data which were generated to investigate the culprit of network security was used. The result showed that the new taxonomy was found to be very efficient and effective to choose the right visualized shape for forensic data for network security. In conclusion, the new taxonomy was proven to be very helpful to choose the right information visualization technique by data characteristics.

• Structural Engineering and Mechanics
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• v.17 no.1
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• pp.1-14
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• 2004

Numerical solution to linear bending analysis of circular plates is obtained by the method of harmonic differential quadrature (HDQ). In the method of differential quadrature (DQ), partial space derivatives of a function appearing in a differential equation are approximated by means of a polynomial expressed as the weighted linear sum of the function values at a preselected grid of discrete points. The method of HDQ that was used in the paper proposes a very simple algebraic formula to determine the weighting coefficients required by differential quadrature approximation without restricting the choice of mesh grids. Applying this concept to the governing differential equation of circular plate gives a set of linear simultaneous equations. Bending moments, stresses values in radial and tangential directions and vertical deflections are found for two different types of load. In the present study, the axisymmetric bending behavior is considered. Both the clamped and the simply supported edges are considered as boundary conditions. The obtained results are compared with existing solutions available from analytical and other numerical results such as finite elements and finite differences methods. A comparison between the HDQ results and the finite difference solutions for one example plate problem is also made. The method presented gives accurate results and is computationally efficient.

• Journal of Power Electronics
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• v.11 no.3
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• pp.311-318
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• 2011

LCL filters installed at converter outputs offer a higher harmonic attenuation than L filters. However, as a three order resonant circuit, it is difficult to stabilize and has a risk of oscillating with the power grid. Therefore, careful design is required to damp LCL resonance. Compared to a passive damping method, an active damping method is a more attractive solution for this problem, since it avoids extra power losses. In this paper, the damping capabilities of capacitor current, capacitor voltage, and grid-side current feedback methods, are analyzed under the discrete-time state-space model. Theoretical analysis shows that the grid-side current feedback method is more suitable for use in active power filters, because it can damp LCL resonance more effectively than the other two methods when the ratio of the resonance and the control frequency is between 0.225 and 0.325. Furthermore, since there is no need for extra sensors for additional states measurements, this method provides a cost-efficient solution. To support the theoretical analysis, the proposed method is tested on a 7-kVA single-phase shunt active power filter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• Journal of Korean Society of Steel Construction
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• v.24 no.3
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• pp.289-299
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• 2012

The goal of this paper is to apply the multi-step Taylor method to a space truss, a non-linear discrete dynamic system, and analyze the non-linear dynamic response and unstable behavior of the structures. The accurate solution based on an analytical approach is needed to deal with the inverse problem, or the dynamic instability of a space truss, because the governing equation has geometrical non-linearity. Therefore, the governing motion equations of the space truss were formulated by considering non-linearity, where an accurate analytical solution could be obtained using the Taylor method. To verify the accuracy of the applied method, an SDOF model was adopted, and the analysis using the Taylor method was compared with the result of the 4th order Runge-Kutta method. Moreover, the dynamic instability and buckling characteristics of the adopted model under step excitation was investigated. The result of the comparison between the two methods of analysis was well matched, and the investigation shows that the dynamic response and the attractors in the phase space can also delineate dynamic snapping under step excitation, and damping affects the displacement of the truss. The analysis shows that dynamic buckling occurs at approximately 77% and 83% of the static buckling in the undamped and damped systems, respectively.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.649-657
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• 2006

Reinforcement Learning is a computational approach to learning whereby an agent take an action which maximize the total amount of reward it receives among possible actions within current state when interacting with a uncertain environment. Q-learning, one of the most active algorithm in Reinforcement Learning, is consist of rewards which is obtained when an agent take an action. But it has the problem with mapping real world to discrete states. When state spaces are very large, Q-learning suffers from time for learning. In constant, when the state space is reduced, many state spaces map to single state space. Because an agent only learns single action within many states, an agent takes an action monotonously. In this paper, to reduce time for learning and complement simple action, we propose the Q-learning using influence map(QIM). By using influence map and adjacent state space's learning result, an agent could choose proper action within uncertain state where an agent does not learn. When this paper compares simulation results of QIM and Q-learning, we show that QIM effects as same as Q-learning even thought QIM uses 4.6% of the Q-learning's state spaces. This is because QIM learns faster than Q-learning about 2.77 times and the state spaces which is needed to learn is reduced, so the occurred problem is complemented by the influence map.