• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.2
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• pp.101-111
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• 2021

In general, several computational resources are required to perform multiple-loading transient response analyses. In this paper, we present the procedure for multiple-loading transient response analysis using the Krylov subspace model order reduction and Newmark's time integration scheme. We utilized ANSYS MAPDL, Python, and ANSYS ACT to automate the transient response analysis procedure in the ANSYS Workbench environment and studied several engineering numerical examples to demonstrate the feasibility and efficiency of the proposed approach.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.217-224
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• 2005

Generally, the underwater flight vehicle (UFV) depth control system operates with the following problems: it is a multi-input multi-output (MIMO) system because the UFV contains both pitch and depth angle variables as well as multiple control planes, it requires robustness because of the possibility that it may encounter uncertainties such as parameter variations and disturbances, it requires a continuous control input because the system that has reduced power consumption and acoustic noise is more practical, and further, it has the speed dependency of controller parameters because the control forces of control planes depend on the operating speed. To solve these problems, an adaptive fuzzy sliding mode controller (AFSMC), which is based on the decomposition method using expert knowledge in the UFV depth control and utilizes a fuzzy basis function expansion (FBFE) and a proportional integral augmented sliding signal, is proposed. To verify the performance of the AFSMC, UFV depth control is performed. Simulation results show that the AFSMC solves all problems experienced in the UFV depth control system online.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.166-172
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• 2005

With the development of RAIM techniques for single failure, increasing interest has been shown in the multiple failure problem. As a result, numerous approaches have been used in attempts to tackle this problem. This paper considers the two failure problem with total least squares (TLS) technique, a solution that has rarely been addressed because TLS requires an immense number of computations. In this paper, the special form of the observation matrix H, (that is, one column is exactly known) is exploited so as to develop an algorithm in a sequential form, thereby reducing computational load. The algorithm permits the advantages of TLS without the excessive computational burden. The proposed algorithm is verified through a numerical simulation.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.358-367
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• 2003

We consider discrete-time factorial Markov Decision Processes (MDPs) in multiple decision-makers environment for infinite horizon average reward criterion with a general joint reward structure but a factorial joint state transition structure. We introduce the "localization" concept that a global MDP is localized for each agent such that each agent needs to consider a local MDP defined only with its own state and action spaces. Based on that, we present a gradient-ascent like iterative distributed algorithm that converges to a local optimal solution of the global MDP. The solution is an autonomous joint policy in that each agent's decision is based on only its local state.cal state.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.736-747
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• 2006

Simultaneous Localization and Map Building(SLAM) is one of the fundamental problems in robot navigation. The Extended Kalman Filter(EKF), which is widely adopted in SLAM approaches, requires extensive computation. The conventional particle filter also needs intense computation to cover a high dimensional state space with particles. This paper proposes an efficient SLAM method based on the recursive unscented Kalman filtering in an environment including a large number of landmarks. The posterior probability distributions of the robot pose and the landmark locations are represented by their marginal Gaussian probability distributions. In particular, the posterior probability distribution of the robot pose is calculated recursively. Each landmark location is updated with the recursively updated robot pose. The proposed method reduces filtering dimensions and computational complexity significantly, and has produced very encouraging results for navigation experiments with noisy multiple simultaneous observations.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.705-713
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• 2006

For the analysis of multiunit extracellular neural signals as multiple spike trains, neural spike sorting is essential. Existing algorithms for the spike sorting have been unsatisfactory when the signal-to-noise ratio(SNR) is low, especially for implementation of fully-automated systems. We present a novel method that shows satisfactory performance even under low SNR, and compare its performance with a recent method based on principal component analysis(PCA) and fuzzy c-means(FCM) clustering algorithm. Our system consists of a spike detector that shows high performance under low SNR, a feature extractor that utilizes projection pursuit based on negentropy maximization, and an unsupervised classifier based on Gaussian mixture model. It is shown that the proposed feature extractor gives better performance compared to the PCA, and the proposed combination of spike detector, feature extraction, and unsupervised classification yields much better performance than the PCA-FCM, in that the realization of fully-automated unsupervised spike sorting becomes more feasible.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.361-364
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• 1997

There has been requested to automate the welding process in shipyard due to its dependence on skilled operators and the inferior working environments. According to these demands, multiple robot welding system for sub-assembly welding line has been developed, realized and installed at Keoje Shipyard. In order to realize automatic welding system, robots have to be equipped with the sensing system to recognize the position of the welding panels. In this research, a camera vision system is developed to detect the position of base panels for subassembly line in shipbuilding. Two camera vision systems are used in two different stages (Mounting and Welding) to automate the recognition and positioning of welding lines. For automatic recognition of panel position, various image processing algorithms are proposed in this paper.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.819-824
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• 1997

This paper presents a cell-based motion control strategy for soccer playing mobile robots. In the central robot motion planner, the planar ground is divided into rectangular cells with variable sizes and motion indices to which direction the mobile robot should move. At every time the multiple objects-the goal gate, ball, and robots-detected, integer values of motion indices are assigned to the cells occupied by mobile robots. Once the indices being calculated, the most desirable state-action pair is chosen from the state and action sets to achieve successful soccer game strategy. The proposed strategy is computationally simple enough to be used for fast robotic soccer system.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1642-1647
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• 2004

In this article, we present the development of the automated system for adjusting the 6 D.O.F circular fixator. The system includes scheduling software to adjust the Hexapod Circular Fixator (HCF) and an automated strut system with the ability of the multiple synchronized motion. HCF was designed to control a 6 degree-of-freedom Ilizarove fixator and it's mechanism is known as the Stewart Platform. HCF scheduler evaluates each value of altered length of the HCF struts to correct the complex skeletal deformity by using the X-ray data of the patient. The data of HCF scheduler feed into the automated strut system which be able to provide the scheduled adjustment and the automated strut is synchronized by input data.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1920-1925
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• 2004

This paper describes a new method for 3D object recognition which used surface segment-based stereo vision. The position and orientation of an objects is identified accurately enabling a robot to pick up, even though the objects are multiple and partially occluded. The stereo vision is used to get the 3D information as 3D sensing, and CAD model with its post processing is used for building models. Matching is initially performed using the model and object features, and calculate roughly the object's position and orientation. Though the fine adjustment step, the accuracy of the position and orientation are improved.