• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.658-662
• /
• 2004

This paper develops a stability analysis and controller synthesis methodology for a continuous-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties. Affine T-S fuzzy system can be an advantage because it may be able to approximate nonlinear functions to high accuracy with fewer rules than the homogeneous T-S fuzzy systems with linear consequents only. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of bilinear matrix inequalities (BMIs). A simulation example is given to illustrate the application of the proposed method.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2006년도 춘계학술발표대회
• /
• pp.23-26
• /
• 2006

기존의 데이터 마이닝 예측 기법 중 회귀분석은 학습 단계에서 생성된 모델을 변경 없이 새로운 데이터에 적용하였다. 그러나 시계열 데이터에 모델 변경 없이 동일하게 적용하면 시간이 지남에 따라 정확도가 낮아지는 단점이 있다. 따라서 이 논문에서는 시간에 따라 변화하는 시계열데이터의 특성을 고려하여 점진적으로 회귀 모델을 갱신하는 기법을 제안한다. 이 기법은 입력되는 모든 데이터를 회귀 모델에 적용하여 점진적으로 모델을 갱신한다. 제안된 기법의 타당성은 RME(Relative Mean Error)와 RMSE(Root Mean Square Error)를 이용하여 측정하였다. 정확도 측정 실험 결과 제안 기법인 IMQR(Incremental Multiple Quadratic Regression) 기법이 MLR(Multiple Linear Regression), MQR(Multiple Quadratic Regression), SVR(Support Vector Regression) 기법에 비해 RME 가 평균 2%, RMSE 가 평균 0.02 정도 우수한 결과를 얻었다.

• Communications for Statistical Applications and Methods
• /
• 제9권3호
• /
• pp.799-808
• /
• 2002

This paper aims at selecting the multi-response design with γ responses minimizing the bias error caused by fitting inadequate models to responses, where the first order models are fitted to Ρ responses fearing the quadratic bias, while to other γ- Ρ responses, the quadratic models are fitted fearing the cubic biases in the cuboidal region of interest. Under the assumption of symmetric design, by minimizing the criterion which represents the amount of error caused by fitting inadequate models, the optimum design was found to be the one having the design moments of second order and the fourth order as 1/3 and l/5, respectively. Examples of the design meeting the required conditions are given for illustration.

• International Journal of Ocean System Engineering
• /
• 제3권1호
• /
• pp.1-9
• /
• 2013

A design procedure for a ship with minimum resistance had been developed using a numerical optimization method called SQP (Sequential Quadratic Programming) combined with computational fluid dynamics (CFD) technique. The frictional resistance coefficient was estimated by the ITTC 1957 model-ship correlation line formula and the wave-making resistance coefficient was evaluated by the potential-flow panel method with the nonlinear free surface boundary conditions. The geometry of the hull surface was represented and modified by B-spline surface modeling technique during the optimization process. The Series 60 ($C_B$=0.60) hull was selected as a parent hull to obtain an optimized hull that produces minimum resistance. The models of the parent and optimized hull forms were tested at calm water condition in order to demonstrate the validity of the proposed methodolgy.

• 품질경영학회지
• /
• 제28권4호
• /
• pp.194-203
• /
• 2000

This paper is concerned with an economic selection of both the process mean and the lower limit for a continuous production process with the quadratic loss function. It is assumed that the quality characteristic is normally distributed with a known variability. A profit model is developed which involves selling price, production cost, reprocessing cost and the cost which is incurred by imperfect quality. Methods of finding optimum values of the process mean and the lower limit are presented, and a numerical example is given.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
• /
• pp.800-802
• /
• 2000

In this paper, we propose the Self-Organizing Networks(SON) based on competitive Fuzzy Polynomial Neuron(FPN) for the optimal design of nonlinear process system. The SON architectures consist of layers with activation nodes based on fuzzy inference rules. Here each activation node is presented as FPN which includes either the simplified or regression Polynomial fuzzy inference rules. The proposed SON is a network resulting from the fusion of the Polynomial Neural Networks(PNN) and a fuzzy inference system. The conclusion part of the rules, especially the regression polynomial uses several types of high-order polynomials such as liner, quadratic and modified quadratic. As the premise part of the rules, both triangular and Gaussian-like membership functions are studied. Chaotic time series data used to evaluate the performance of our proposed model.

• 제어로봇시스템학회논문지
• /
• 제13권4호
• /
• pp.377-384
• /
• 2007

This paper studies on the relation between linearization methods and controller gains in the looper ILQ(lnverse Linear Quadratic optimal control) system for hot strip finishing mills. Firstly, two linear models arc respectively derived by a linearization method using Taylor's series expansion and a static state feedback linearization method, respectively, and the linear models are compared with the nonlinear model. Secondly, the looper servo controllers are respectively designed on the basis of two linearization models. Finally, the relation between the performances of two ILQ servo controllers and the linearization methods, and the structures and control gains of two controllers are evaluated by a computer simulation.

• 제어로봇시스템학회논문지
• /
• 제20권8호
• /
• pp.828-834
• /
• 2014

This paper presents a comparison among three types of approaches to an ARC (Active Roll Control) with an AARB(Active Anti-Roll Bar) for a vehicle system. Lateral acceleration and road profile are considered as disturbance. The ARC is designed with an LQ SOF (Linear Quadratic Static Output Feedback) control, $H_{\infty}$ control and SMC (Sliding Mode Control). These approaches are compared in terms of rollover prevention and ride comfort. For comparison, Bode plot analysis based on linear model and frequency response analysis based on CarSim simulation are performed.

• Journal of the Korean Data and Information Science Society
• /
• 제21권4호
• /
• pp.813-818
• /
• 2010

The least squares estimation method for model parameters under failure step-stress accelerated life tests is studied and a numerical example will be given to illustrate the proposed inferential procedures under the compound linear plans proposed as an alternative to the optimal quadratic plan, assuming that the exponential distribution with a quadratic relationship between stress and log-mean lifetime. The proposed compound linear plan for constant stress accelerated life tests and 4:2:1 plan are compared for various situations. Even though the compound linear plan was proposed under constant stress accelerated life tests, we found that this plan did well relatively in failure step-stress accelerated life tests.

• 제어로봇시스템학회논문지
• /
• 제15권7호
• /
• pp.655-660
• /
• 2009

In many real applications, the discrepancy problem between controller outputs and plant inputs or the abrupt variation problem of controller outputs can occur. These problems have a negative effect on control performance and stability. It is well-known that two phenomena called 'windup' and 'bump' cause these problems. So far these problems have been studied separately in each side of the anti-windup and the bumpless transfer. This paper proposes a new unified method combines the anti-windup and the bumpless transfer method using the linear quadratic minimization and a proper state space model representation for the anti-windup controller. The proposed method has a feature that it takes account of both the anti-windup and the bumpless transfer in one formula. Finally, we exemplify the performance of the proposed method via numerical examples using the controller switching between the anti-windup PID controller and the anti-windup LQ controller.