• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.1
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• pp.181-186
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• 2009

In this paper, the stability analysis for uncertain dynamic systems with time-varying delays is considered. By constructing a new Lyapunov functional, a novel stability criterion is established in terms of linear matrix inequalities (LMIs). Two numerical examples are carried out to support the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.231-234
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• 1996

This paper considers the output regulation problems on uncertain systems. Using NR-estimator(on-line), a family of equilibrium points for the uncertain system is computed. The state variables of the closed loop system track the average value of the obtained equilibrium manifold by dynamic state feedback control.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.39.2-39
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• 2001

This paper describes the design of an output-feedback controller based on an adaptive fuzzy observer for uncertain single-input single-output nonlinear dynamical systems. Especially, we have focused on the realization of minimal dynamic order of the adaptive fuzzy observer. For the purpose, we propose a new method in which no strictly positive real(SPR) condition is needed and combine dynamic rule activation scheme with on-line estimation of fuzzy parameters. By using proposed scheme, we can reduce computation time, storage space, and dynamic order of the adaptive fuzzy observer ...

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.54-67
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• 2003

In this paper, a novel estimation technique for a robust adaptive control scheme is presented for a class of uncertain nonlinear systems with a general set of uncertainty. For a class of introduced more extended semi-strict feedback forms which generalize the systems studied in recent years, a novel estimation technique is proposed to estimate the states of the fully nonlinear unmodeled dynamics without stringent conditions. With the introduction of powerful functions, the estimation error can be tuned to a desired small region around the origin via the estimator parameters. In addition, with some effective functions, a modified adaptive backstepping for dynamic uncertainties is presented to drive the output to an arbitrarily small region around the origin by an appropriate choice of the design parameters. With our proposed schemes, we can remove or relax the assumptions of the existing results.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.159-162
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• 1997

This paper describes robust stabilization of nonlinear single-input uncertain systems without matching conditions. We consider nonlinear systems with a vector of unknown constant parameters perturbed about a known value. The approach utilizes the generalized controller canonical form to lump the unmatched uncertainties recursively into the matched ones. This can be achieved via nonlinear coordinate transformations which depend not only on the states of the nonlinear system but also on the control input. Then the dynamic robust control law is derived and the stability result is also presented.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.128-133
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• 1998

This paper aims to present some ideas for implementation of Uncertain Relational Databases (URD) which are extensions of classical relational databases. Our system firstly is based on possibility distribution and probability theory to represent and manipulate fuzzy and probabilistic information, secondly adopts flexible mechanisms that allow the management of uncertain data through the resources provided by both available relational database management systems and front-end interfaces, and lastly chooses dynamic SQL to enhance versatility and adjustability of systems.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.207-211
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• 2004

We consider a class of uncertain nonlinear systems containing the uncertainties without a priori information except that they are bounded. For such systems, we assume that the upper bound of the uncertainties is represented as a Fredholm integral equation of the first kind and we propose an adaptation law that is capable of estimating the upper bound. Using this adaptive upper bound, a continuous robust control which renders uncertain nonlinear systems uniformly ultimately bounded is designed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.153-158
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• 1999

We consider single-input nonlinear systems with unknown unmodelled time-varying parameters or disturbances which are bounded. The main goal is to identify classes of uncertain systems for which the control exist and to provide constructive design procedures. Assuming that the undisturbed nominal system ( ,g) is partially state feedback linearizable, that a strict triangularity condition, a linear parametrization condition, and {{{{ { G}_{r-1 } }}}} hold for the uncertain terms, and that some condition is satisfied in the transformed partially linear system, we design an adaptive regulating dynamic control. At first, we identify classes of nonlinear uncertain systems and give a systematic procedure for the design of a robust regulation for the nonlinear systems.