• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1197-1200
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• 2010

The problem of designing a nonlinear sliding surface for an uncertain system is considered. The proposed sliding surface comprises a linear time invariant term and an additional time varying nonlinear term. It is assumed that a linear sliding surface parameter matrix guaranteeing the asymptotic stability of the sliding mode dynamics is given. The linear sliding surface parameter matrix is used for the linear term of the proposed sliding surface. The additional nonlinear term is designed so that a Lyapunov function decreases more rapidly. By including the additional nonlinear term to the linear sliding surface parameter matrix we obtain a nonlinear sliding surface such that the speed of responses is improved. We also give a switching feedback control law inducing a stable sliding motion in finite time. Finally, we give an LMI-based design algorithm, together with a design example.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.272-272
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• 2000

since the controller is part or the overall closed-Loop system, it is necessary that the designed controller be able to tolerate some uncertainty in its coefficients. The adequate stability and performance margins are required for the designed nominal controllers. In the paper. we study the method to design the non-fragile fixed-structured controller for real parametric uncertain systems. When we impose the controller parameter perturbation, the structure of the controller must be given. Therefore, we assume that the controller has fixed-structure. The fixed-structure controller is practically necessary especially when the robust controller synthesis results in a high-order controller. In SISO systems, we propose the robust controller design method using the Mapping theorem. In the method, the plant uncertainty and controller Parameter are of the multilineal form in the stability and performance conditions. Then, the controller synthesis problem is easily recast to Linear Programming Problem.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.9-11
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• 1998

Most of sensorless algorithms are based on motor equations including electrical and mechanical parameters. However, parameter variation and uncertain error decrease the accuracy of speed estimation of PMSM. This paper investigates the sensorless speed control of PMSM considering parameter variation. The proposed algorithm use the speed compensator which is robust in parameter variation and error. The simulation and experimental results indicate good performances.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.625-628
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• 2011

This paper presents an LMI-based method to design an integral sliding mode controller for a class of uncertain systems with unmatched uncertainties. The uncertain system under consideration may have unmatched parameter uncertainties in the state matrix as well as in the input matrix. Using LMIs an existence condition of a sliding surface is derived. And a switching feedback control law is given. Finally, numerical examples are given to show that the proposed method can be better than the existing results for some cases.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.8
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• pp.1441-1443
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• 2010

This paper presents an LMI-based method to design an integral sliding mode controller for for a class of uncertain systems with mismatched unstructured uncertainties. The uncertain system under consideration may have mismatched parameter uncertainties in the state matrix as well as in the input matrix. Using LMIs we derive an existence condition of a sliding surface. And we give a switching feedback control law. Finally, we give a numerical design example in order to show that the proposed method can be better than the existing results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.6
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• pp.1542-1550
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• 1994

For a class of singularly perturbed uncertain system, an output feedback control law is designed. The controller structure is designed based on the uncertain reduced-order system, and the controller parameters are determined by information on the reduced-order and full-order systems. It has been shown that the reduces-order system with the designed controller possesses a stability property(specifically, a global uniform attractivity). Furthermore, the stability property of this control scheme is robust with respect to singular perturbation ; i.e., the full-order system, subject to the same controller, possesses the global uniform attractivity, provided the singular perturbation parameter $\mu<\mu^{*}$, where a threshold value $\mu^{*}$ can be computed from the information available on the full-order system.

• 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 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2986-2999
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• 2019

The uncertainties of the uncertain graph make the traditional definition and algorithms on mining dense graph for certain graph not applicable. The subgraph obtained by maximizing expected density from an uncertain graph always has many low edge-probability data, which makes it low reliable and low expected edge density. Based on the concept of ${\beta}$-subgraph, to overcome the low reliability of the densest subgraph, the concept of optimal ${\beta}$-subgraph is proposed. An efficient greedy algorithm is also developed to find the optimal ${\beta}$-subgraph. Simulation experiments of multiple sets of datasets show that the average edge-possibility of optimal ${\beta}$-subgraph is improved by nearly 40%, and the expected edge density reaches 0.9 on average. The parameter ${\beta}$ is scalable and applicable to multiple scenarios.

• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.484-491
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• 2003

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear. time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.