• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• Clean Technology
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• v.20 no.4
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• pp.449-456
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• 2014

There has been increasing concerns for the problems of water security in countries, caused by the frequent occurrence of localized drought due to the climate change and uncertainty of water balance. The importance of fresh water is emphasized as considerable amount of usable fresh water is utilized for power generation sector producing electricity. PV power system, the source of renewable energy, consumes water for the every steps of life cycle: manufacturing, installation, and operation. However, it uses relatively less water than the traditional energy sources such as thermal power and nuclear power sources. In this study, to find out the use of water for the entire process of PV power system from extracting raw materials to operating the system, the footprint of water in the whole process is measured to be analyzed. Measuring the result, the PV water footprint of value chain was $0.989m^3/MWh$ and the water footprint appeared higher specially in poly-Si and solar cell process. The following two reasons explain it: poly-Si process is energy-intensive process and it consumes lots of cooling water. In solar cell process, deionized water is used considerably for washing a high-efficiency crystalline silicon. It is identified that PV system is the source using less water than traditional ones, which has a critical value in saving water. In discussing the future energy policy, it is vital to introduce the concept of water footprint as a supplementary value of renewable energy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1624-1632
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• 2009

In this study, we introduce the design methodology of an optimized Interval Type-2 fuzzy controller. The fixed MF design of type-1 based FLC leads to the difficulty of rule-based control design for representing the linguistically uncertain expression. In the Type-2 FLC as the expanded type of Type-1 FLC, we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. Type-2 FLC has a robust characteristic in the unknown system with unspecific noise when compared with Type-1 FLC. Through computer simulation as well as practical experiment, we compare their performance by applying both the optimized Type-1 and Type-2 fuzzy cascade controllers to ball and beam system. To evaluate each controller performance, we consider controller characteristic parameters such as maximum overshoot, delay time, rise time, settling time and steady-state error.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1769-1770
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• 2008

Type-2 퍼지 논리 시스템은 기존의 Type-1 퍼지 논리 시스템으로부터 확장된 개념으로서 언어적 불확실성에 대한 개념을 부곽시킨다. Type-2 퍼지 논리 시스템의 가장 큰 특징은 멤버쉽 함수에 Footprint Of Uncertainty(FOU)을 사용하여 불확실성을 표현한다. Type-2 퍼지 논리 시스템은 그것의 rule-base 안에서 최소한 한 개 이상의 Type-2 멤버쉽 함수(MF)를 포함한다. Type-2 퍼지 로직 제어기는 MF가 FOU를 포함하여 계산량이 많은 반면에 외란에 대하여 강인한 성격을 지닌다. 따라서 본 논문에서는 비선형성이 강한 볼빔 시스템에 Type-1과 Type-2 퍼지 로직 제어기를 설계하고 외란에 대하여 견실한 제어기를 보인다.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.785-799
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• 2022

The aim of this study was to characterize the emission pathways and the footprint of greenhouse gases (GHG) in Daecheong Reservoir using the G-res Tool, and to evaluate the GHG emission intensity (EI) compared to other energy sources. In addition, the change in GHG emissions was assessed in response to the total phosphorus (TP) concentration. The GHG flux in post-impoundment was found to be 262 gCO₂eq/m²/yr, of which CO₂ and CH₄ were 45.7% and 54.2%, respectively. Diffusion of CO₂ contributed the most, followed by diffusion, degassing, and bubbling of CH₄. The net GHG flux increased to 510 gCO₂eq/m²/yr because the forest (as CO₂ sink) was lost after dam construction. The EI of Daecheong Reservoir was 86.8 gCO₂eq/kWh, which is 3.7 times higher than the global EI of hydroelectric power, due to its low power density. However, it was remarkable to highlight the value to be 9.5 times less than that of coal, a fossil fuel. We also found that a decrease in TP concentration in the reservoir leads to a decrease in GHG emissions. The results can be used to improve understanding of the GHG emission characteristics and to reduce uncertainty of the national GHG inventory of dam reservoirs.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.3
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• pp.308-316
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• 2013

This paper proposes an observation model for a particle filter-based localization using a sonar grid map. The proposed model estimates a predicted observation by considering the properties of a sonar sensor which has a large angular uncertainty. The proposed model searches a grid which has the highest probability to reflect a sonar beam using the following procedures; (1) the reliable area of a single sonar data is determined using the footprint association model; (2) the detection probability of each grid cell in a sonar beam coverage in estimated. The proposed model was applied to the particle filter based localization, and was verified by experiments in indoor environments.

• Atmosphere
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• v.25 no.2
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• pp.193-203
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• 2015

A large aperture scintillometer (LAS) was deployed with an optical path length of 2.1 km to estimate turbulent sensible heat flux (${\mathcal{Q}}_H$) over a highly heterogeneous urban area. Scintillation measurements were conducted during cold season in November and December 2013, and the daytime data of 14 days were used in the analysis after quality control processes. The LAS-derived ${\mathcal{Q}}_H$ show reasonable temporal variation ranging $20{\sim}160W\;m^{-2}$ in unstable atmospheric conditions, and well compare with the measured net radiation. The LAS footprint analysis suggests that ${\mathcal{Q}}_H$ can be relatively high when the newly built-up urban area has high source contribution of the turbulent flux in the study area ('northwesterly winds'). Sensitivity tests show that the LAS-derived ${\mathcal{Q}}_H$ are highly sensitive to non-dimensional similarity function for temperature structure function parameter, but relatively less sensitive to surface aerodynamic parameters and meteorological variables (temperature and wind speed). A lower Bowen ratio also has a significant influence on the flux estimation. Overall uncertainty of the estimated daytime ${\mathcal{Q}}_H$ is expected within about 20% at an upper limit for the analysis data. It is also found that stable atmospheric conditions can be poorly determined when the scintillometry technique is applied over the highly heterogeneous urban area.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1871_1872
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• 2009

본 논문 에서는 Type-2 퍼지 논리 시스템을 설계하고, 불확실한 정보를 갖는 입력 데이터에 대하여 Type-1 퍼지 논리 시스템과 성능을 비교한다. Type-1 퍼지 논리 시스템은 외부 잡음에 민감한 단점을 가지고 있는 반면, Type-2 퍼지 논리 시스템은 불확실한 정보를 잘 표현 할 수 있다. 따라서 Type-2 퍼지 논리 시스템을 이용하여 이러한 단점을 극복하고자 2가지의 모델을 설계한다. 첫 번째 모델은 규칙의 전 후반부가 Type-1 퍼지 집합으로 구성된 Type-1 퍼지 논리 시스템을 설계 한다. 두 번째는 규칙 전 후반부에 Type-2 퍼지 집합으로 구성된 Type-2 퍼지 논리 시스템을 설계한다. 여기서 규칙 전반부의 입력 공간 분할 및 FOU(Footprint Of Uncertainty)형성에는 FCM(Fuzzy C_Means) clustering 방법을 사용하고, 입자 군집 최적화(Particle Swarm Optimization) 알고리즘을 사용하여 최적의 파라미터를 설계한다. 본 논문 에서는 또한 입력 데이터에 인위적으로 가하는 노이즈에 따른 각각 모델의 성능을 비교한다. 마지막으로 비선형 모델 평가에 주로 사용되는 NOx 데이터를 제안된 모델에 적용하고, 실험을 통하여 노이즈가 첨가되고, 불확실한 정보를 다루기에 Type-1 퍼지 논리 시스템 보다 Type-2 퍼지 논리 시스템이 효율적이라는 것을 보인다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.972-980
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• 2010

In this study, we introduce the design methodology of an optimized type-2 fuzzy cascade controller with the aid of hierarchical fair competition-based genetic algorithm(HFCGA) for ball & beam system. The ball & beam system consists of servo motor, beam and ball, and remains mutually connected in line in itself. The ball & beam system determines the position of ball through the control of a servo motor. Consequently the displacement change of the position of the moving ball and its ensuing change of the angle of the beam results in the change of the position angle of a servo motor. The type-2 fuzzy cascade controller scheme consists of the outer controller and the inner controller as two cascaded fuzzy controllers. In type-2 fuzzy logic controller(FLC) as the expanded type of type-1 fuzzy logic controller(FLC), we can effectively improve the control characteristic by using the footprint of uncertainty(FOU) of membership function. The control parameters(scaling factors) of each fuzzy controller using HFCGA which is a kind of parallel genetic algorithms(PGAs). HFCGA helps alleviate the premature convergence being generated in conventional genetic algorithms(GAs). We estimated controller characteristic parameters of optimized type-2 fuzzy cascade controller applied ball & beam system such as maximum overshoot, delay time, rise time, settling time and steady-state error. For a detailed comparative analysis from the viewpoint of the performance results and the design methodology, the proposed method for the ball & beam system which is realized by the fuzzy cascade controller based on HFCGA, is presented in comparison with the conventional PD cascade controller based on serial genetic algorithms.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.7
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• pp.51-60
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• 2002

The Monte-Carlo simulation of statistical analysis is used to investigate the final conditions of states as well as the footprint boundaries resulting from the atmospheric re-entry dispersions. The re-entry dispersions in this paper are specified by a $7\times7$ covariance matrix of latitude, longitude, altitude, bank angle, flight path angle, heading error, and range at entry velocity. The error sources that affect these at re-entry for a deboost are the uncertainties associated with atmospheric density and temperature, initial errors, wind, and estimation error of aerodynamic coefficients. Using $3{\sigma}_n$ deviations of these errors and a nominal flight trajectory, the covariance matrix of state variables can be determined by performing a trajectory error analysis. Major considerations in the application of the Monte-Carlo method are the simulation of perturbed trajectories, bank reversal, and determination of the impact points for each of these trajectories. This paper analyzes the results of uncertainties from the viewpoint of aero-coefficients and bank reversal.