• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.2112-2115
• /
• 2005

This paper considers the synthesis of non-fragile $H_{\infty}$ state feedback controllers for singular systems and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile $H_{\infty}$ controller, and the measure of non-fragility in controller are presented via LMI(linear matrix inequality) technique. Also, through singular value decomposition, some changes of variables, and Schur complements, the sufficient condition can be rewritten as LMI form in terms of transformed variables. Therefore, the obtained non-fragile $H_{\infty}$ controller guarantees the asymptotic stability and disturbance attenuation of the closed loop singular systems within a prescribed degree. Finally, a numerical example is given to illustrate the design method.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
• /
• pp.981-986
• /
• 1988

A controller synthesis procedure for precise tracking of reference inputs in the sense of spheres is applied to a 3 d.o.f. robotic manipulator. This methodology applies to a class of nonlinear systems with input uncertainty and parameter uncertainty. The 3 d.o.f. manipulator to be controlled is subjected to varying payloads and is required to follow specified joint trajectories to within prespecified tolerances. The design procedure above lends itself naturally to this type of control problem. The appeal of such a design procedure lies on a special decomposition which exploits linear control theory on the one hand and facilitates a separate treatment of the effects of nonlinearities and the uncertainties on the other.

• Wind and Structures
• /
• 제11권1호
• /
• pp.51-70
• /
• 2008

CFD is applied to evaluate pedestrian wind comfort at outdoor platforms in a high-rise apartment building. Model validation is focused on generic building sub-configurations that are obtained by decomposition of the actual complex building geometry. The comfort study is performed during the design stage, which allows structural design changes to be made for wind comfort improvement. Preliminary simulations are performed to determine the effect of different design modifications. A full wind comfort assessment study is conducted for the final design. Structural remedial measures for this building, aimed at reducing pressure short-circuiting, appear to be successful in bringing the discomfort probability estimates down to acceptable levels. Finally, the importance of one of the main sources of uncertainty in this type of wind comfort studies is illustrated. It is shown that the uncertainty about the terrain roughness classification can strongly influence the outcome of wind comfort studies and can lead to wrong decisions. This problem is present to the same extent in both wind tunnel and CFD wind comfort studies when applying the same particular procedure for terrain relation contributions as used in this paper.

• 한국전자통신학회논문지
• /
• 제7권5호
• /
• pp.1133-1138
• /
• 2012

본 논문은 최적제어에 기초하여 비선형 슬라이딩 평면을 설계하는 것이다. 최적제어입력에 의한 상태 궤적을 Frobenius 정리와 matrix decomposition 방법에 의해 구하였고, 이 궤적을 시스템의 슬라이딩 평면으로 설정하였다. 상태는 초기부터 슬라이딩 평면을 유지하며, 그 결과 초기상태 단계로부터 전 영역까지 시스템의 강인성은 보장 받을 수 있으며, 도달시간 동안 발생 될 수 있는 불확실성과 외란의 영향을 제거되고, 큰 제어 입력의 문제도 해결할 수 있었다. 그리고 최적경로를 슬라이딩 평면으로 설정함으로 추적시간을 줄일 수 있었다. 역진자 시스템을 사용하여 그 타당성을 보인다.

• Journal of Electrical Engineering and Technology
• /
• 제12권6호
• /
• pp.2166-2176
• /
• 2017

Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.

• Asia-Pacific Journal of Atmospheric Sciences
• /
• 제54권4호
• /
• pp.611-622
• /
• 2018

Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.

• Structural Monitoring and Maintenance
• /
• 제8권4호
• /
• pp.379-402
• /
• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• 전자공학회논문지SC
• /
• 제41권3호
• /
• pp.9-16
• /
• 2004

본 논문에서는 시변 시간지연을 가지는 특이시스템에 대한 관측기 기반 Η∞ 출력궤환 제어기 설계방법을 단 하나의 선형행렬부등식 조건을 이용하여 제시한다. 제어기가 존재할 충분조건과 제어기 설계방법을 모든 변수의 견지에서 완벽한 하나의 선형행렬부등식으로 표현하여 볼록최적화가 가능하도록 한다. 제어기의 설계과정은 제안한 하나의 충분조건으로부터 직접 구해진다. 구한 충분조건은 하나의 선형행렬부등식으로 표현되어지므로, 슈어 여수정리와 변수치환 및 특이치 분해의 기법에 의하여 궤환이득과 추정이득을 포함하는 모든 해로부터 관측기 기반 Η∞ 출력궤환 제어기를 동시에 구할 수 있다. 또한 제안한 알고리듬을 이용하여 파라미터 불확실성과 시간지연을 가지는 특이시스템에 대한 관측기 기반 견실 Η∞ 출력제환 제어기 설계도 가능함을 보인다. 마지막으로, 제안한 알고리듬의 타당성을 수치예제를 통하여 확인한다.

• Smart Structures and Systems
• /
• 제17권2호
• /
• pp.209-230
• /
• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.

• 한국연소학회:학술대회논문집
• /
• 한국연소학회 2006년도 제33회 KOSCO SYMPOSIUM 논문집
• /
• pp.42-45
• /
• 2006

A new and reusable energy source is water-treatment sludges. There is a significant need for understanding the characteristics of sludge combustion related to improving efficiency and ensuring the safety of this new energy source. Because sludges are composed of solids and gas mixture, the combustion of the mixture may become quite complex. Not only decomposition of conventional organic elements but also dust explosion may be important during the process of converting sludges into a new and safe form of energy. Sludge combustion mainly involves hydrogen, methane, hydro carbons, carbon, and organic particles. Dust explosion during the gasification stage may depend on the surrounding temperature and the composition of gases. The uncertainty in the explosive behavior of energetic source is noted in this work. We study the explosion characteristics of sludge combustion while the reusability of sewage sludges as a new form of energy is also investigated.