• Journal of Industrial Technology
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• v.10
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• pp.3-8
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• 1990

This paper presents a linear state feedback control approach to the stabilization of discrete-time uncertain systems with bounded uncertain parameters. The approach is based on the LQ(linear quadratic) regulator theory and Lyapunov's stability analysis. Asymptotically stable behavior is guaranteed in the presence of parameter uncertainties, and the upper bound of the performance index is determined.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.477-481
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• 1993

The aim of this paper is to analyze via computer simulation the robust performance of TDF(Two Degree of Freedom) H.$_{\infty}$ controller for uncertain systems having parameter uncertainty. We apply the TDF H$_{\infty}$ controller to autopilot design. We evaluate the robust performance of the TDF H$_{\infty}$ controller for uncertain systems and present the guaranteed bound of robust performance via computer simulation.on.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1085-1090
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• 1989

In this paper, an adaptive control method is presented to guarantee the ultimate boundedness of uncertain systems with partially known uncertainty bounds. This method, with a conventional linear compensator, is used to improve the performance of the trajectory tracking of a robotic manipulator with uncertainties. The proposed method is simulated under several different environments, and its performance is compared with the computed torque method. The simulation results show that the proposed method is well suited for high-performance operation of uncertain robotic systems.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.18-25
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• 2012

IChinese postman problem is one of the classical combinatorial optimization problems with many applications. However, in application, some uncertain factors are frequently encountered. This paper employs uncertain programming to deal with Chinese postman problem with uncertain weight Within the framework of uncertainty theory, the concepts of expected shortest route, ${\alpha}$-shortest route, and distribution shortest route are proposed. After that, expected shortest model, and ${\alpha}$-shortest model are constructed. Taking advantage of properties of uncertainty theory, these models can be transf-ormed into their corresponding deterministic forms, which can be solved by classical algorithm..

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.55-59
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• 1991

This paper presents a method for designing a full state feedback linear static control law. This will stabilize a given linear uncertain system and also guarantee the performance of the system. The uncertain systems are described by state equation which contains uncertain parameters in system and input distribution matrices. The method is based on the guaranteed cost control of Chang and Peng(1972). The controller gain can be obtained by the solution of a algebraic Riccati equation in which the input weighting matrices depend on the uncertainty bounds. The algebraic Riecati equation in this paper is same as that of weighted LQ regulator problem.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.271-274
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• 1995

This paper is concerned with the problem of robust stabilization of uncertain single-input and single-output nonlinear systems. Based on the input/output linearization approach for nonlinear state feedback synthesis in conjunction with Lyapunov methods, a stabilizing state feedback controller is proposed. Compared with the controllers reported in the control literature, instead of uniform ultimate boudedness, the controller proposed in this paper can guarantee uniform asymptotic stability of nonlinear systems in the presence of uncertainties. The required information about uncertain dynamics in the system is only that the uncertainties are bounded in Euclidean norm by known functions of the system state.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.6
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• pp.397-402
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• 2016

This paper proposes a robust tracking control for constrained uncertain linear systems by combining a disturbance observer (DOB) and linear matrix inequality (LMI) based state feedback control. To this end, the state feedback control is designed for the nominal system and then a DOB based feed-forward control is added to reject uncertainties. In doing so, the DOB and state feedback controller are joined in a way that the combined control satisfies the input constraints and closed loop stability is guaranteed. Simulation results are provided to show that the proposed control scheme successfully stabilizes uncertain systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.840-847
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• 2009

This paper deals with an $H_{\infty}$ output feedback controller design for uncertain singularly perturbed T-S fuzzy systems. Integral quadratic constraints are used to describe various kinds of uncertainties of the plant. It is shown that the $H_{\infty}$ norm of the uncertain singularly perturbed fuzzy system is less than $\gamma$ for a sufficiently small $\varepsilon$ > 0 if the $H_{\infty}$ norms of both the slow and fast subsystem are less than $\gamma$. Using this fact, we develop a linear matrix inequality based design method which is independent of the singular perturbation parameter $\varepsilon$. A numerical example is provided to demonstrate the efficacy of the proposed design method.