• Journal of Advanced Marine Engineering and Technology
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• v.11 no.2
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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.

• Proceedings of the KIEE Conference
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• 2004.07d
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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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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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.

• Proceedings of the KIEE Conference
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• 2003.07d
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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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• v.3 no.4
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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.

• Journal of Advanced Navigation Technology
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• v.6 no.2
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• pp.119-129
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• 2002

Maneuvering targets are difficult to track for the Kalman filter since the target model of tracking filter might not fit the real target trajectory and the statistical characteristics of the target maneuver are unknown in advance. In order to track such a highly maneuvering target, several schemes have been proposed and improved the tracking performance in some extent. Among those tracking schemes the Input Estimation (IE), Variable Dimension (VD) and Turning Acceleration Estimator (TAE) became popular. However, so far their tracking performances were analyzed individually and were not compared. In this paper, the tracking performances of the typical IE, VD and TAE schemes for a maneuvering target are compared. Monte-Carlo Simulations for three maneuvering profiles are carried out and the results are analyzed towards practical applications.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.11
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• pp.5841-5846
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• 2013

In this work, we consider the effect of doppler bandwidth on the performance of channel sounding. We develop the mathematical formulation of the problem and compare the MMSE channel estimator to the simple correlator. Examples of the performance of the MMSE and correlator estimators are presented for the single-input single-output (SISO) case with various values of Doppler bandwidth to assess the impact of time variation. The results show that as the $f_dT$ product increases the performance of both the MMSE and correlator estimates gets worse, and that the performance of the MMSE estimator improves relative to the correlator.We also consider case that the exact statistics of the channel are unknown It is shown that when the mismatch is not too large, the MMSE estimator with mismatch still does better than the simple correlator, but if the mismatch is large, then the correlator can do better.

• Structural Monitoring and Maintenance
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• v.6 no.4
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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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• v.29 no.4
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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.