• 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.

• 전력전자학회논문지
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• 제6권4호
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• pp.38-38
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• 2001

The three-phase diode rectifier with capacitive filter is highly sensitive to line voltage unbalance. Because of its inherent nonlinear characteristics, small line voltage unbalance may cause highly unbalanced line current, causing detrimental effects on power quality. This paper presents a theoretical basis on this ′unbalance amplification effect′ and derives an analytical model of line current characteristics under unbalanced line voltage condition for various modes of operation. The results provide a basic guideline for optimal design of a three-phase diode rectifier with capacitive filter that is most commonly used for interfacing various power conversion equipments to power lines.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 B
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• pp.643-645
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• 1999

In between of linear and nonlinear systems lies a large class of bilinear systems. The major importance of bilinear systems lies in the applications to the real world systems such as many physical processes, many biological process, some economic process. Despite vast application of bilinear systems they have not been studied extensively in the domain of singularly perturbations except for a few minor results. In this paper we will utilize singular peturbations theory to obtain the closed-loop optimal solution for discrete-time bilinear systems.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.384-386
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• 2009

This paper introduces an effectively optimized Fuzzy model identification by means of complex and nonlinear system applying PSO algorithm. In other words, we use PSO(Particle Swarm Optimization) for identification of Fuzzy model structure and parameter. PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. This paper identifies the premise part parameters and the consequence structures that have many effects on Fuzzy system based on PSO. In the premise parts of the rules, we use triangular. Finally we evaluate the Fuzzy model that is widely used in the standard model of gas data and sew data.

• 한국생산제조학회지
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• 제26권3호
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• pp.313-319
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• 2017

This study presents a genetic algorithm (GA) to design a PID controller systematically for an inchworm operated by piezoelectric actuators. The performance index considering overshoot and settling time is adopted to search an optimal PID gain using GA. The piezoelectric actuator shows nonlinear characteristics including hysteresis and residual displacement. The PID feedback system combined with an integrator is used to improve the ability of tracking the complex input signals and suppressing the steady state error. The PID controller tuned by GA can track the various motion contours effectively. However, the PID controller shows an improper residual vibration under the application of high-frequency square input. The input shaper combined with the feedback system can overcome this limitation of the PID controller.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.268-272
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• 2007

These days many scientists make studies of feedback control system for stability on non-linear state and for the maneuver of flying objects. These feedback control systems have to satisfy trajectory condition and angular conditions, that is to say, controllability and stability simultaneously to achieve mission. In this paper, a design methods using model based control system which consists of spiral predictive model, Q-function included into generalized-work function is shown. It is made a clear that the proposed algorithm using SPM maneuvers for controllability and stability at the same time is successful in attaining our purpose. The feature of the proposed algorithm is illustrated by simulation results. As a conclusion, the proposed algorithm is useful for the control of moving objects.

• 한국해양공학회지
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• 제18권3호
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• pp.32-39
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• 2004

A design procedure for a ship with minimum total resistance has been developed using a numerical optimization method called SQP(sequential quadratic programming) to search for different optimal hull forms. The frictional resistance has been estimated using the ITTC 1957 model-ship correlation line formula, and the wave resistance has been evaluated using a potential-flow panel method that is based on Rankine sources with nonlinear free surface boundary conditions. The geometry of a hull surface has been modified using B-spline surface patches, during the whole optimization process. The numerical analyses have been carried out for the modified Wilgey hull at three different speeds (Fn=0.25, 0.316, 0.408), and the calculation results were compared.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.103-108
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• 2003

In this paper, the current lead for superconducting device is studied by numerical method. The current lead is cooled by surrounded $N_{2}$ gas by natural convection. The heat conduction equation for current lead and boundary layer equation for $N_{2}$ gas must be solved simultaneously. The boundary layer equation for $N_{2}$ gas is highly nonlinear for varied temperature of current lead. So the linearization method is adopted for simplicity. Numerical results using natural convection cooling are compared with the conventional cooling methods such as conduction cooling and vapor cooling methods. The main difference of natural convection cooing is the non-zero temperature gradient at the top of current lead for the minimum heat dissipation into superconducting devices. For the optimized conduction-cooling and vapor-cooling current leads, the temperature gradient at the top of current lead is zero. Also, the heat flow at the cold end is much smaller than conduction cooling case.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.1
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• pp.252-255
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• 2003

The pulsed laser deposition process modeling is investigated using neural networks based on radial basis function networks and multi-layer perceptron. Two input factors are examined with respect to the PL intensity. In order to minimize the joint confidence region of fabrication process with varying the conditions, D-optimal experimental design technique is performed and photoluminescence intensity is characterized by neural networks. The statistical results were then used to verify the fitness of the nonlinear process model. Based on the results, this modeling methodology can be optimized process conditions for pulsed laser deposition process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.229-229
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• 2000

Conventional gain-tuning methods such as Ziegler-Nickels methods, have many disadvantages that optimal control ler gain should be tuned manually. In this paper, modified PID controllers which include self-tuning characteristics are proposed. Proposed controllers automatically tune the PID gains in on-1ine using neural networks. A new learning scheme was proposed for improving learning speed in neural networks and satisfying the real time condition. In this paper, using a nonlinear mapping capability of neural networks, we derive a tuning method of PID controller based on a Back propagation(BP)method of multilayered neural networks. Simulated and experimental results show that the proposed method can give the appropriate parameters of PID controller when it is implemented to DC Motor.