• 센서학회지
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• 제28권4호
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• pp.216-220
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• 2019

In this paper, we propose a finite memory filter (estimator) for discrete-time stochastic linear systems with delays in state and measurement. A novel filtering algorithm is designed based on finite memory strategies, to achieve high estimation accuracy and stability under parametric uncertainties. The new finite memory filter uses a set of recent observations with appropriately chosen initial horizon conditions. The key contribution is the derivation of Lyapunov-like equations for finite memory mean and covariance of system state with an arbitrary number of time delays. A numerical example demonstrates that the proposed algorithm is more robust and accurate than the Kalman filter against dynamic model uncertainties.

• 대한조선학회논문집
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• 제54권3호
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• pp.227-241
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• 2017

In this study, a Volterra system for the variations of metacentric height (GM) in waves is employed to simulate the parametric roll phenomena of ships in head sea condition. Using the present Volterra system, the transfer function of each harmonic component in the GM variation is computed for different ship models, including mathematical models and a real containership, and the results are validated through the comparison with the values obtained using the direct calculations based on a weakly nonlinear time-domain method. Then, a semi-analytic approach employing a 1-degree of freedom equation for roll motion is developed to simulate the parametric roll motions in irregular waves. In the derived approach, the nonlinear and time-varying restoring forces in the waves are approximated using the Volterra system. Through simulations of the parametric roll for different sea states, the effects of the 1st and 2nd-order harmonic components of the variations in the occurrence and amplitude of the parametric roll motions are investigated. Because of the strong nonlinearities in the phenomena, a stochastic analysis is conducted to examine the statistical properties of the roll motions in consideration of the sensitivities and uncertainties in the computations.

• Journal of Mechanical Science and Technology
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• 제15권4호
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• pp.433-440
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• 2001

A new design of the sliding mode control is proposed for the uncertain linear time-varying second order system. The proposed control drives system states to the target point in the minimum time with specified ranges of parametric uncertainties and disturbances. One of the advantages of the proposed control scheme is that the control inputs do not go beyond saturation limits of the actuators. The other advantage is that the minimum arrival time and the acceleration of the second order actuators system can be estimated with given parametric bounds and can be expressed in the closed from; conversely, the designer can select actuators based on the condition of the minimum arrival time to the target point. The superior performance of the proposed control scheme to other sliding mode controllers is validated by computer simulations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.89-91
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• 2005

In this paper, we propose a robust visual feedback controller with integral action for tracking control of n-link robot manipulators in the presence of constant bounded parametric uncertainties. The proposed control input has robustness to the parametric uncertainty and reduces tracking error in the steady-state. The stability of the closed-loop system is shown by Lyapunov method. The effectiveness of the proposed method is shown by simulation results on the 5-link robot manipulators with two degree of freedom.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.313-323
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• 2014

Sensor fault detection and isolation problems subject to H_/$H_{\infty}$, performance are concerned for linear time-invariant systems with time delay in a state and parametric uncertainties. To that end, a model-based observer bank approach is pursued. The design conditions for both continuous- and discrete-time cases are formulated in terms of matrix inequalities, which are then converted to the problems solvable via an algorithm involving convex optimization.

• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.407-422
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• 2004

A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

• Coupled systems mechanics
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• 제6권4호
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• pp.487-499
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• 2017

This paper investigates the approximate solution bounds of radon diffusion equation in soil pore matrix coupled with uncertainty. These problems have been modeled by few researchers by considering the parameters as crisp, which may not give the correct essence of the uncertainty. Here, the interval uncertainties are handled by parametric form and solution of the relevant uncertain diffusion equation is found by using Galerkin's Method. The shape functions are taken as the linear combination of orthogonal polynomials which are generated based on the parametric form of the interval uncertainty. Uncertain bounds are computed and results are compared in special cases viz. with the crisp solution.

• 제어로봇시스템학회논문지
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• 제15권11호
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• pp.1071-1075
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• 2009

This article describes a robust control method by using peak control of a sensitivity function in the state-feedback control systems. This method apparently reduces the peak, and as a result makes closed loop systems more stable. The designed closed loop systems also make the response to an external step disturbance more fast with a lower undershoot. At the conclusion, it is verified that the proposed method enhances robust stability and robust performance to parametric uncertainties through $\mu$-plot.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.251-257
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• 2007

For the modern aircraft, uncertainty has bee an important issue to its aeroelastic stability. Therefore, many researches have been conducted regarding this topic. The uncertainties in the aeroelastic system amy consist of the structural and aerodynamic uncertainty. In this paper, we suggest a parametric uncertainty modeling and conduct the aeroelastic stability analysis of a typical wing including the uncertainty.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2747-2749
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• 2005

This paper presents an intelligent control system for an ac servo motor dirve to track periodic commands using a neural network. AC servo motor drive system is rather similar to a linear system. However, the uncertainties, such as machanical parametric variation, external disturbance, uncertainty due to nonideal in transient state. therefore an intelligent control system that isan on-line trained neural network controller with adaptive learning rates.