• Journal of Advanced Marine Engineering and Technology
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• 제11권2호
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• pp.61-70
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• 1987

미지의 조작량이나 매우 큰 외란이 입력으로 작용하고 있는 동력시스템의 정도 높은 상태를 추정하려면 상태추정에 앞서 시스템의 입력추정이 요구된다. 본 논문에서는 간략형 칼만필터 (SKF:Simplified Kalman Filter)를 이용하여 운동하고 있는 목표물의 상태추정을 행함과 동시에 기동탐지자 (Maneuvering Detector)와 입력추정자 (Input Estimator)에 의해 시스템의 입력을 추정하고 이것에 의하여 SKF의 추정치를 보정해줌으로써 입력이 미지인 동적 시스템의 상태추정에 있어서 추정정도를 개선하는 방법을 제안하며 디지탈계산기를 이용한 시뮤레이션을 통하여 본 방법의 유효성을 밝힌다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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• pp.2182-2184
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• 2004

This paper presents a systematic and straightforward fault estimation approach for process fault detection. isolation and accommodation. The approach includes the design of a reduced-order observer and an algebraic-fault estimator. The observer is designed for an unknown input and fault-free system, which is obtained by coordinate transformations of original systems with unknown inputs and faults. The observer information is devoted to- the fault estimation for fault detection and isolation. The fault estimates can be used to form an additional control input to accommodate the fault. The suggested scheme is verified through simulation studies performed on the control of a vertical takeoff and landing (VTOL) aircraft in the vertical plane.

• 대한전기학회논문지:전력기술부문A
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• 제48권8호
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• pp.996-1003
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• 1999

This paper propose a position-speed controller with an estimator which can estimate states and disturbance. The overall control system consists of two parts: the position-speed controller and an estimator. The Kalman filter applied as state-feedback controller is an optimal state estimator applied to a dynamic system that involves random perturbations and gives a linear, unbiased and minimum error variance recursive algorithm to optimally estimate the unknown state. Therefore, we consider the error problem about the servo system modeling and the measurement noise as a stochastic system and implement a optimal state observer, and enhance the estimate performance of position and speed using that. Using two-degree-of freedom(TDOF) conception, we design the command input response and the closed loop characteristics independently. The servo system is to improve the closed loop characteristics without affecting the command imput response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer using a inverse-transfer matrix. Therefore, the performance of overall position-speed controller is enhanced. Finally, the performance of the proposed controller is exemplified by some simulations and by applying the real servo system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2200-2202
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• 2003

In this paper, differentiation operational matrix for Haar function is derived. Proposed method only using a matrix calculation of Haar discrete matrix and block-pulse function's integration operational matrix. It would be possible to use to design an a1gebraic estimator for fault detection or unknown input observer effectively.

• Transactions on Control, Automation and Systems Engineering
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• 제3권4호
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• pp.289-292
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• 2001

This paper concerns with a receding horizon estimator (RHE) for discrete-time linear systems subject to constraints on the estimate. In solving the optimization for every horizons, the past all measurement data outside the horizon is discarded and thus the arrival cost is not considered. The RHE in the current work is a finite impulse response (FIR) structure which has some good inherent properties. The proposed RHE can be represented in the simple matrix form for the unconstrained case. Various numerical examples demonstrate how including constraints in the RHE can improve estimation performance. Especially, in the application to the unknown input estimation, it will be shown how the FIR structure in the RHE can improve the estimation speed.

• 한국항행학회논문지
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• 제6권2호
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• pp.119-129
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• 2002

기동표적의 추적은 실제의 표적 궤적과 기동의 통계적 특성을 미리 알 수 없기 때문에 매우 어려운 일이다. 이를 해결하기 위한 여러 가지 기법들이 제안되었고 이들 방식은 과거의 고전적인 방법에 비해 상당한 성능향상을 가져왔다. 이들 중에서 많이 사용되고 있는 방법은 입력추정, 가변차원 및 회전가속도 추정기를 사용하는 필터이다. 이들에 대한 성능은 각각 해석되어 왔으나 비교 분석되지 않았다. 본 논문에서는 칼만필터를 기본으로 한 이들 필터에 대하여 추적 성능을 비교한다. 실제적인 기동표적의 추적에 용이하게 적용할 수 있도록 3가지 종류의 회전 기동에 대해 Monte-Carlo 시뮬레이션을 수행하고 그 결과를 비교 분석함으로써 각 필터에 대한 특성을 해석한다.

• Transactions on Control, Automation and Systems Engineering
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• 제2권2호
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• pp.110-115
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• 2000

A receding horizon FIR filter is suggested for discrete time-varying systems, combining the Kalman filter with the receding horizon strategy. The suggested filter is shown to be an FIR structure that has many good ingerent properties. The suggested filter is represented in an iterative form and also in a standard FIR form. The suggested filter turns out to be a remarkable deadbeat observer that is often robust against system and measurement noises. It is also shown that the suggested filter is an unbiased estimator irrespective of any horizon initial condition. For the amenability to parallel and systolic implementation as well as the numerical stability, a square-root algorithm for the suggested filter is presented. To evaluate performance, the suggested filter is applied to a problem of unknown input estimation and compared with the existing Kalman filter based approach.

• 한국산학기술학회논문지
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• 제14권11호
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• pp.5841-5846
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• 2013

본 연구에서는 도플러 대역폭이 채널 사운딩에 미치는 영향을 고려한다. 이를 위해 먼저 수학적인 공식을 전개한 후에 단순한 상관기와 MMSE를 비교한다. 시간 변화의 영향을 평가하기 위하여 MMSE와 상관기의 성능은 SISO 환경하에서 다양한 도플러 대역폭 값을 적용하여 분석한다. 시뮬레이션 결과를 통하여 $f_dT$ 값이 증가할수록 MMSE와 상관기의 성능은 더 열화되며 MMSE의 성능은 상관기에 비해 향상됨을 보인다 또한 정확한 채널 정보가 알려져 있지 않을 경우의 성능 열화에 대해서도 고려한다. 채널 정보의 부정확도가 낮을 경우에는 여전히MMSE의 성능이 좋지만 채널 정보의 부정확성이 커질수록 상관기의 성능이 더 좋아짐을 보인다. 본 연구는 기존에 직관적으로 시행해 왔던 MMSE와 성관기의 성능 분석을 위한 시뮬레이션에 추가적으로 수학적인 접근법을 제공하여 그 응용분야를 넓혀 갈 수 있음을 보인다.

• Structural Monitoring and Maintenance
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• 제6권4호
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• Smart Structures and Systems
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• 제29권4호
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• pp.617-624
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• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.