• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.109-141
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• 1998

Many processes in the industrial realm exhibit sstochastic and nonlinear behavior. Consequently, an intelligent system must be able to nonlinear production processes as well as probabilistic phenomena. In order for a knowledge based system to control a manufacturing processes as well as probabilistic phenomena. In order for a knowledge based system to control manufacturing process, an important capability is that of prediction : forecasting the future trajectory of a process as well as the consequences of the control action. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes, includinb chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a chaotic process in the presence of various patterns of noise.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.767-779
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• 2017

Automated mission planning for unmanned aerial vehicles (UAVs) is difficult because of the propagation of several sources of error into the solution, as for any large scale autonomous system. To ensure reliable system performance, we quantify all sources of error and their propagation through a mission planner for operation of UAVs in an obstacle rich environment we developed in prior work. In this sequel to that work, we show that the mission planner developed before can be made robust to errors arising from the mapping, sensing, actuation, and environmental disturbances through creating systematic buffers around obstacles using the calculations of uncertainty propagation. This robustness makes the mission planner truly autonomous and scalable to many UAVs without human intervention. We illustrate with simulation results for trajectory generation of multiple UAVs in a surveillance problem in an urban environment while optimizing for either maximal flight time or minimal fuel consumption. Our solution methods are suitable for any well-mapped region, and the final collision free paths are obtained through offline sub-optimal solution of an mTSP (multiple traveling salesman problem).

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.491-493
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• 2011

Traffic sign detection is the domain of automatic driver assistant systems. There are literatures for traffic sign detection using color information, however, color-based method contains ill-posed condition and to extract the region of interest is difficult. In our work, we propose a method for traffic sign detection using k-means clustering method, back-propagation neural network, and projection histogram features that yields the robustness for ill-posed condition. Using the color information of traffic signs enables k-means algorithm to cluster the region of interest for the detection efficiently. In each step of clustering, a cluster is verified by the neural network so that the cluster exactly represents the location of a traffic sign. Proposed method is practical, and yields robustness for the unexpected region of interest or for multiple detections.

• Smart Structures and Systems
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• v.6 no.1
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• pp.57-72
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• 2010

This paper presents the most significant results obtained within a broad-ranging experimental program aiming to evaluate both the effectiveness and the robustness of a Base Isolation (BIS) and a Tuned Mass Damper (TMD) combined control strategy (BI & TMD). Following a brief description of the experimental model set-up and the adopted kinematic scaling technique, this paper describes the identification procedures carried out to characterize the system''s model. The dynamic response of a small-scale model to recorded earthquake excitations, which has been scaled by using the Buckingham pi-theorem, are later presented and discussed. Finally, the effectiveness and robustness of the combined control strategy is evaluated by comparing the model's dynamic response. In particular, reduction in relative displacements and absolute accelerations due to the application of different mass damping systems is investigated.

• Advances in robotics research
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• v.1 no.2
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• pp.171-183
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• 2014

Distributed planning and decision making can be beneficial from the robustness, adaptability and fault tolerance in multi-robot systems. Distributed mechanisms have not been employed in three dimensional transportation systems namely aerial and underwater environments. This paper presents a distributed cooperation mechanism on multi robot transportation problem in three dimensional environments. The cooperation mechanism is based on artificial capital market, a newly introduced market based negotiation protocol. In the proposed mechanism contributing in transportation task is defined as asset. Each robot is considered as an investor who decides if he is going to invest on some assets. The decision is made based on environmental constraint including fuel limitation and distances those are modeled as capital and cost. Simulations show effectiveness of the algorithm in terms of robustness, speed and adaptability.

• Journal of Astronomy and Space Sciences
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• v.26 no.4
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• pp.651-658
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• 2009

Nonlinear sliding surface design in variable structure systems for spacecraft attitude control problems is studied. A robustness analysis is performed for regular form of system, and calculation of actuator bandwidth is presented by reviewing sliding surface dynamics. To achieve non-singular attitude description and minimal parameterization, spacecraft attitude control problems are considered based on modified Rodrigues parameters (MRP). It is shown that the derived controller ensures the sliding motion in pre-determined region irrespective of unmodeled effects and disturbances.

• Journal of KIISE:Information Networking
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• v.36 no.6
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• pp.536-544
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• 2009

This paper proposed a novel vector digital watermarking method to protect copyright. The proposed method embeds watermarks after finding the closest pair of points and calculating the distance of the points. We tested the robustness of the method through several attacks on watermarked data. The experimental results show that the proposed method has more robustness than previous methods. And the new method doesn't change the topology of the vector data. Therefore, this method can be 'the vector digital watermarking for GIS.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.1
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• pp.132-138
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• 1999

This paper addresses an analytical approach to the mechanical error analysis of gear train and tolerance design and manufacture of gear train in restricted space considering motor driving torque, driving system inertia, motor acceleration, motor rotor inertia and friction torque. The gear train is designed to have optimum gear ratio in restricted space and each gear is manufactured to have the lowest weight and each gear tooth is heat-treated to have robustness. Based on the small difference between the mechanical error analysis and measurement, gear train design with optimum gear ratio and restricted space and robustness is proposed

• Journal of Power Electronics
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• v.9 no.3
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• pp.456-463
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• 2009

The paper presents a method for controlling induction motors using a nonlinear internal model control (IMC) approach. The process model and the inverse model are developed in the rotor flux coordinate. The main advantage of the proposed method is that it easily specifies the performance (steady state error, transient response, etc.) and the robustness of the controller by means of the IMC filters. Simulation results illustrate the effectiveness of the proposed method. Results on a real time system show that the control system has good performance and robustness against changes in motor parameters (rotor and stator resistances, rotor and stator inductances, rotor inertia).

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.497-499
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• 1999

This paper considers enhancing the robustness of a MIMO(Multi-Input Multi-Output) predictive control system. The characteristic polynomial matrix of the closed-loop is shown to consist of two factors $P_c$ and T, where $P_c$ is determined by the tuning knobs of the predictive controller and T is an observer or prefilter polynomial matrix. The robust stability condition is derived in terms of $P_c$ and T. A guideline on the selection of T is then presented for open-loop stable processes.