• 한국정밀공학회지
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• 제30권4호
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• pp.427-433
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• 2013

Stair climbing is one of critical issues for field robots to widen applicable areas. This paper presents optimal design on kinematic parameters of a new robotic platform for stair climbing. The robotic platform climbs various stairs by body-flip locomotion with caterpillar type main platform. Kinematic parameters such as platform length, platform height, and caterpillar rotation speed are optimized to maximize stair-climbing stability. Three types of stairs are used to simulate typical user conditions. The optimal design process is conducted based on Taguchi methodology, and resulting parameters with optimized objective function are presented. In near future, a prototype is assembled for real environment testing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.4987-5005
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• 2017

This paper introduces a new method to solve Similarity Recognition for Cloth Products, which is based on Fuzzy logic and Particle swarm optimization algorithm. For convenience, it is called the SRCPFP method hereafter. In this paper, the SRCPFP method combines Fuzzy Logic (FL) and Particle Swarm Optimization (PSO) algorithm to solve similarity recognition for cloth products. First, it establishes three features, length, thickness, and temperature resistance, respectively, for each cloth product. Subsequently, these three features are engaged to construct a Fuzzy Inference System (FIS) which can find out the similarity between a query cloth and each sampling cloth in the cloth database D. At the same time, the FIS integrated with the PSO algorithm can effectively search for near optimal parameters of membership functions in eight fuzzy rules of the FIS for the above similarities. Finally, experimental results represent that the SRCPFP method can realize a satisfying recognition performance and outperform other well-known methods for similarity recognition under considerations here.

• 정보저장시스템학회논문집
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• 제5권1호
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• pp.41-46
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• 2009

In SIL-based NFR servo systems, the residual error and the overshoot that are occurred in the process of the modes-witching servo which consists of approach, gap-control modes, and safety mode are reduced by using PID controller. However, the design method of conventional PID controller is not sufficient for the stable air gap control system. Therefore, the optimal PID controller using LQR manner is more useful to find the designed parameters of PID controller. In this paper, we show that the performance of the optimal PID controller is better than that of the lead-lag controller.

• 한국경영과학회지
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• 제20권3호
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• pp.105-122
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• 1995

Based on linear models, the inference about the true measurement x$_{f}$ and the optimal designs x (nx1) for the calibration experiments are considered via Baysian statistical decision analysis. The posterior distribution of x$_{f}$ given the observation y$_{f}$ (qxl) and the calibration experiment is obtained with normal priors for x$_{f}$ and for themodel parameters (.alpha., .betha.). This posterior distribution is not in the form of any known distributions, which leads to the use of a numerical integration or an approximation for the calculation of the overall expected loss. The general structure of the expected loss function is characterized in the form of a conjecture. A near-optimal design is obtained through the approximation nof the conditional covariance matrix of the joint distribution of (x$_{f}$ , y$_{f}$ $^{T}$ )$^{T}$ . Numerical results for the univariate case are given to demonstrate the conjecture and to evaluate the approximation.n.

• Smart Structures and Systems
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• 제30권1호
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• pp.89-106
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• 2022

The negative stiffness of an active or semi-active damper system has been proven to be very effective in reducing dynamic response. Therefore, energy dissipation devices possessing negative stiffness, such as viscous inertial mass dampers (VIMDs), have drawn much attention recently. The control performance of the VIMD for cable vibration mitigation has already been demonstrated by many researchers. In this paper, a new optimal design procedure for VIMD parameters for taut cable vibration control is presented based on the fixed-points method originally developed for tuned mass damper design. A model consisting of a taut cable and a VIMD installed near a cable end is studied. The frequency response function (FRF) of the cable under a sinusoidal load distributed proportionally to the mode shape is derived. Then, the fixed-points method is applied to the FRF curves. The performance of a VIMD with the optimal parameters is subsequently evaluated through simulations. A taut cable model with a tuned VIMD is established for several cases of external excitation. The performance of VIMDs using the proposed optimal parameters is compared with that in the literature. The results show that cable vibration can be significantly reduced using the proposed optimal VIMD with a relatively small amount of damping. Multiple VIMDs are applied effectively to reduce the cable vibration with multi-modal components.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.114-116
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• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• Smart Structures and Systems
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• 제20권1호
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Smart Structures and Systems
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• 제17권5호
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• pp.709-724
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• 2016

This study investigates the optimum design parameters of a superelastic friction base isolator (S-FBI) system through a multi-objective genetic algorithm to improve the performance of isolated buildings against near-fault earthquakes. The S-FBI system consists of a flat steel-PTFE sliding bearing and superelastic NiTi shape memory alloy (SMA) cables. Sliding bearing limits the transfer of shear across the isolation interface and provides damping from sliding friction. SMA cables provide restoring force capability to the isolation system together with additional damping characteristics. A three-story building is modeled with S-FBI isolation system. Multiple-objective numerical optimization that simultaneously minimizes isolation-level displacements and superstructure response is carried out with a genetic algorithm in order to optimize S-FBI system. Nonlinear time history analyses of the building with optimal S-FBI system are performed. A set of 20 near-fault ground motion records are used in numerical simulations. Results show that S-FBI system successfully control response of the buildings against near-fault earthquakes without sacrificing in isolation efficacy and producing large isolation-level deformations.

• 산업경영시스템학회지
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• 제15권26호
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• pp.99-109
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• 1992

This paper presents a cost model of the system which is managed under a continuous review (Q,r) policy at each retailer and peridic review (R,T) policy at the central warehouse. An iterative procedure is performed to find the optimal or near-optimal' solution for the policy parameters at each retailers and a central warehouse in this study.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.394-397
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• 1987

This paper presents an analysis of the man-machine control system. A man-machine system depends on the performance of a human operator for proper operation. The analysis method is based upon the assumption that human operator will act in a near optimal controller. Optimal control theory and its associated state space representation is used as the basis for the analytic procedure. The computer simulation for a given plant shows that plant parameters have limited range by the human operator.