• Journal of Power System Engineering
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• v.4 no.3
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• pp.72-80
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identification. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identification are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identity the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2690-2692
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identifcation. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identifcation are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identify the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.687-690
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• 1991

In deterministic design of feedback controllers for uncertain dynamical systems, the bound on the uncertainty is an important clue to guarantee the asymptotic stability or uniform ultimate boundedness of the closed-loop system. In this paper, using only the measurable output we propose an adaptation law for the estimation of the bound of the uncertainty. And based on this adaptation law an adaptive control which renders the uncertain dynamical systems uniformly ultimately bounded is constructed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.372-377
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• 1993

In this paper, we investigate a set-membership identification approach to the quantification of an upper bound of model uncertainty in frequency domain, which is required in the H$_{\infty}$ robust control system design. First we formulate this problem as a set-membership identification of a nominal model error in the presence f unknown noise input with unknown bound, while the ordinary set-membership approaches assume that an upper bound of the uncertain input is known. For this purpose, the proposed algorithm includes the estimation of the bound of the uncertain input. thus the proposed method can obtain the hard bound of the model error in frequency domain as well as a parametric lower-order nominal model. Finally numerical simulation results are shown to confirm the validity of the presented algorithm..

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.32-43
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• 1999

Adaptive robust control scheme is introduced for flexible joint manipulator with nonlinearities and uncertainties. The system does not satisfy the matching condition due to insufficient actuators for each node. The control only relies on the assumption that the bound of uncertainty exists. Thus, the bounded value does not need to be known a prior. The control utilizes the update law by estimating the bound of the uncertainties. The control scheme uses the backstepping method and constructs a state transformation. Also, stability analysis is done for both transformed system and original system.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.51-58
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• 2023

Geofencing supports unmanned aerial vehicle (UAV) operation by defining stay-in and stay-out regions. National Aeronautics and Space Administration (NASA) has developed a prototype of the geofencing function, SAFEGUARD, which prevents stayout region violation by utilizing position estimates. Thus, SAFEGUARD depends on navigation system performance, and the safety risk associated with the navigation system uncertainty should be considered. This study presents a methodology to compute the safety risk assessment-based along-track position error bound under nominal and Global Navigation Satellite Systems (GNSS) failure conditions. A Kalman filter system using pseudorange measurements as well as pseudorange rate measurements is considered for determining the position uncertainty induced by velocity uncertainty. The worst case pseudorange and pseudorange rate fault-based position error bound under the GNSS failure condition are derived by applying a Receiver Autonomous Integrity Monitor (RAIM). Position error bound simulations are also conducted for different GNSS fault hypotheses and constellation conditions with a GNSS/INS integrated navigation system. The results show that the proposed along-track position error bounds depend on satellite geometries caused by UAV attitude change and are reduced to about 40% of those of the single constellation case when using the dual constellation.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.463-465
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• 1998

In this paper, we consider the problem of robust stability of large-scale uncertain linear systems with time-varying delays. The considered uncertainties are both unstructured uncertainty which is only known its norm bound and structured uncertainty which is known its structure. Based on Lyapunov stability theorem and $H_{\infty}$ theory. we present uncertainty upper bound that guarantee the robust stability of systems. Especially, robustness bound are obtained directly without solving the Lyapunov equation. Finally, we show the usefulness of our results by numerical example.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.117-119
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• 1997

We consider the control design for nonlinear uncertain systems. The uncertainty is mismatched and possibly fast time-varying. Within the suitable range of the uncertainty the control is valid. No statistical information on uncertainty is imposed. Only the possible bound of the uncertain parameter is known and the control design is based on Lyapunov approach.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.608-613
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• 2017

In this paper, we consider the stability bound for uncertainty of delayed state variables in the linear discrete interval time-varying systems with time-varying delay time. The considered system has an interval time-varying system matrix for non-delayed states and is perturbed by the unstructured time-varying uncertainty in delayed states with time-varying delay time within fixed interval. Compared to the previous results which are derived for time-invariant cases and can not be extended to time-varying cases, the new stability bound in this paper is applicable to time-varying systems in which every factors are considered as time-varying variables. The proposed result has no limitation in applicable systems and is very powerful in the aspects of feasibility compared to the previous. Furthermore. the new bound needs no complex numerical algorithms such as LMI(Linear Matrix Inequality) equation or upper solution bound of Lyapunov equation. By numerical examples, it is shown that the proposed bound is able to include the many existing results in the previous literatures and has better performances in the aspects of expandability and effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.9
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• pp.658-663
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• 2003

In deterministic design of feedback controllers for uncertain dynamic systems, the upper bound of the uncertainty is very important to guarantee the stability of the closed loop system. In this paper, we assume that the upper bound of the uncertainty is formulated using a Fredholm integral equation of the first kind, that is, an integral of the product of a predefined kernel with an unknown influence function. We propose an adaptation law that is capable of estimating this upper bound. Using this adaptive upper bound, we design an adaptive variable structure control (AVSC), which guarantees asymptotic stability/ultimate boundedness of uncertain dynamic systems. The illustrative example shows the proposed AVSC is effective for uncertain dynamic systems.