• Interaction and multiscale mechanics
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• 제5권3호
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• pp.211-228
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• 2012

This paper reports the development of a generalized inverse analysis formulation for the parameter estimation of four-parameter Burger model. The analysis is carried out by formulating the problem as a mathematical programming formulation in terms of identification of the design vector, the objective function and the design constraints. Thereafter, the formulated constrained nonlinear multivariable problem is solved with the aid of fmincon: an in-built constrained optimization solver module available in MatLab. In order to gain experience, a synthetic case-study is considered wherein key issues such as the determination and setting up of variable bounds, global optimality of the solution and minimum number of data-points required for prediction of parameters is addressed. The results reveal that the developed technique is quite efficient in predicting the model parameters. The best result is obtained when the design variables are subjected to a lower bound without any upper bound. Global optimality of the solution is achieved using the developed technique. A minimum of 4-5 randomly selected data-points are required to achieve the optimal solution. The above technique has also been adopted for real-time settlement of four oil refineries with encouraging results.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2240-2245
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• 2003

In this paper, the controller design by coefficient diagram method (CDM) for controlling the trolley position, load-swing angle and hoisting rope length of the overhead crane system simultaneously is proposed. The overhead crane system is a MIMO system consisting of two inputs and three outputs. Its mathematical model is nonlinear with coupling characteristics. This nonlinear model can be approximated to obtain a linear model where the first input mainly affects the trolley position and the load-swing angle while the second input mainly affects the hoisting rope length. In order to utilize the CDM concept for assigning the controllers, namely PID, PD and PI controllers separately, the model is approximated to be three transfer functions in accordance with trolley position, the load-swing angle and the hoisting rope length controls respectively. The satisfied performances of the overhead crane system controlled by the these controllers and fast rejection of the disturbance effect occurred at the trolley position are shown by simulation and experimental results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.670-677
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• 1991

All models of dynamical systems invariably have some measure of uncertainties associated with some of their dynamics. The recent approaches to establish robustness of stabilizing feedback control against the possible uncertainties have a serious limitation, that is, their applicability only to the systems that satisfy the matching conditions. Such conditions are rarely met in general applications. If a particular system satisfies the matching conditions, the addition of an actuator will destroy the satisfaction of such conditions. In this paper, we develop robust control algorithm for uncertain multivariable systems in which the matching conditions are not necessarily met. In order to eliminate an influence over partial state variables due to unknown constant disturbances we perform the appropriate block-decomposition for a given system. Functional observers are introduced to estimate the unknown constant disturbances. The sliding mode controller is designed in such a way that the partial state variables in the state-space are directed towards switching surfaces and regulated to the origin asymptotically. Numerical examples are discussed as illustrations.

• 한국정밀공학회지
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• 제15권12호
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• pp.128-141
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• 1998

We propose the robust nonlinear controller design methodology for the multivariable system which has hard nonlinearities (Coulomb friction, dead-zone, etc) and the structured real parameter uncertainty. The hard nonlinearity can be linearized by the RIDF technique and structured real parameter uncertainty can be modelled as the sense of Peterson-Hollot's quadratic Lyapunov bound. For this system, we apply the robust QLQG/H$_{\infty}$ control and then can obtain four Riccati equations. Because of the system's nonlinearity, however, one Riccati equation contains the nonlinear correction term that is very difficult to solve numerically, In order to treat this problem, using some transformations to Riccati equations, the nonlinear correction term can be eliminated. Then, only two Riccati equations need to design a controller. Finally, the robust nonlinear controller is synthesized via IRIDF techniques. To test this proposed control method, we consider the direct-drive robot manipulator system that has Coulomb frictions and varying inertia.

• 한국도로학회논문집
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• 제19권4호
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• 대한의용생체공학회:의공학회지
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• 제27권6호
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• pp.301-309
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• 2006

The main purpose of this study is to derive a regression equation that predicts the individual differences in activity energy expenditure (AEE) using accelerometer during different types of activity. Two subject groups were recruited separately in time: One is a homogeneous group of 94 healthy young adults with age ranged from $20\sim35$ yrs. The other subject group has a broad spectrum of physical characteristics in terms of age and fat ratio. 226 adolescents and adults of age ranged from $12\sim57$ yrs and fat ratio from $4.1\sim39.7%$ were in the second group. The wireless 3-axis accelerometers were developed and carefully fixed at the waist belt level. Simultaneously the total calorie expenditure was measured by gas analyzer. Each subject performed walking and running at speeds of 1.5, 3.0, 4.5, 6.0, 6.5, 7.5, and 8.5 km/hr. A generalized sensor-independent regression equation for AEE was derived. The regression equation was developed fur walking and running. The regression coefficients were predicted as functions of physical factors-age, gender, height, and weight with multivariable regression analysis. The generalized calorie estimation equation predicts AEE with correlation coefficient of 0.96 and the average accuracy of the accumulated calorie was $89.6{\pm}7.9%$.

• 대한전기학회논문지
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• 제36권7호
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• pp.501-513
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• 1987

다변수 비선형시스텝의 각 출력을 독립적으로 제어하기 위한 방식에는 decoupling과 decomposition 두가지 방식이 있는데 기존 연구에서는 이 두 개념의 구별이 분명하지 않다. 본 논문에서는 보다 실용적인 decomposition 방식에 대한 여러 분제들을 고찰한다. decoupling과 decomposition 의 근본적 차이점을 분명히 하고 새 연구결과로서 decomposition 을 통하여 각 출력의 독립제어를 가능하게 하는 비선형 되먹임 제어법칙들을 모두 찾아낸다. 이들 비선형 되먹임 제어법칙들은 특수구조를 갖는 `표준분해시스템`을 통하여 간단하게 표시되어 질 수 있다. 본 연구의 중요성을 강조하기 위하여 한 간단한 예를 든다.

• Journal of the Korean Data and Information Science Society
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• 제28권3호
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• pp.709-720
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• 2017

In healthcare and medical research, many important variables have a measurement error such as body mass index and laboratory data. It is also not easy to collect samples of large size because of high cost and long time required to collect the target patient satisfied with inclusion and exclusion criteria. Beside, the demand for solving a complex scientific problem has highly increased so that a semiparametric regression approach could be of substantial value solving this problem. To address the issues of measurement error, small domain and a scientific complexity, we conduct a multivariable Bayesian smoothing under structural measurement error covariate in this article. Specifically we enhance our previous model by incorporating other useful auxiliary covariates free of measurement error. For the regression spline, we use a radial basis functions with fixed knots for the measurement error covariate. We organize a fully Bayesian approach to fit the model and estimate parameters using Markov chain Monte Carlo. Simulation results represent that the method performs well. We illustrate the results using a national survey data for application.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.449-454
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• 1994

The Stewart Platform is one example of a motion simulator which generater 6DOF motion in space by six actuators in parallel. The presented control methrol of 6DOF motion simulator is generally classified into two types, one is SISO and the other is MIMO control type. The SISO control can't compensate for external load variation and different dynamic behavior of 6DOF motion, trerefore this type don's control motion precisely. On the other hand, the MIMO control compensates for a interference of 6DOF motion because MIMO controller is designed with 6DOF motion simulator synamics. But MIMO control of motion simulator has a complexity of 6DOF displacement feedback, because in oder to obtain feedback value we must solve the forward kinematics using measurement of cylinder length or design a state estimator, unless measurement of 6DOF displacement is possible. In this paper, a multivariable controller using H .inf. optimal control theory is designed to consider a interference of 6DOF motion and to obtain robust,precise control of system. Also in order to solve the mentioned problem of MIMO control, this paper presents a modified MIMO control model which control 6DOF motion by using feedback of measurement od cylinder length.

• 한국정밀공학회지
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• 제26권10호
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• pp.65-73
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• 2009

For mass production of printed electronics in roll-to-roll fashion, precision tension control is important to reduce register errors. Register error should be minimized within several to tens of microns for many electronic devices to be manufactured through printing technology. In order to achieve this goal, tension disturbance must be attenuated before printing process within a certain range. In this paper, a certain tension range which allows maintaining register error within 10 micron was defined with specific operating conditions. A LQG controller was proposed instead of the conventional PI controller for precision tension control using a multivariable feedback. A guideline to determine design parameters for calculating LQ gain was proposed. The proposed LQG controller was compared to both PI controller and LQ regulator with white noise by numerical simulations. Results showed that the proposed LQG controller was effective for attenuating tension disturbance with white noise.