Yan Shi

Kyushu Tokai University, Kumamoto, Kumamoto Prefecture, Japan

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Publications (31)6.85 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, new results are established for the delay-independent and delay-dependent problems of dissipative analysis and state-feedback synthesis for a class of nonlinear systems with time-varying delays with polytopic uncertainties. This class consists of linear time-delay systems subject to nonlinear cone-bounded perturbations. Both delay-independent and delay-dependent dissipativity criteria are established as linear matrix inequality-based feasibility tests. The developed results in this paper for the nominal system encompass available results on H∞ approach, passivity and positive realness for time-delay systems as special cases. All the sufficient stability conditions are cast. Robust dissipativity as well as dissipative state-feedback synthesis results are also derived. Numerical examples are provided to illustrate the theoretical developments.
    Journal of the Franklin Institute. 01/2009;
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    ABSTRACT: A delay-dependent analysis and synthesis approach is established for a class of linear discrete-time switched delay systems with convex bounded parameter uncertainties in all system matrices. New results are established for both constant and time-varying delays using switched Lyapunov–Krasovskii functionals. A delay-dependent analysis of the uncertain switched delay system is developed to guarantee that it is asymptotically stable with an ℒ2 gain smaller than a prescribed constant level. Delay-dependent switched control feedback is then designed, based on state and output measurements, to render the corresponding switched closed-loop system delay-dependent asymptotically stable with a prescribed ℒ2 gain measure. The developed results are cast as linear matrix inequalities (LMIs) and tested on representative examples.
    Circuits Systems and Signal Processing 01/2009; 28(5):735-761. · 0.98 Impact Factor
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    ABSTRACT: In this paper, we investigate a class of linear continuous-time systems with Markovian jump parameters. An integral part of the system dynamics is a delayed state with time-varying and bounded delays. The jumping parameters are modeled as a continuous-time, discrete-state Markov process. Employing norm-bounded parametric uncertainties and utilizing the second-method of Lyapunov, we examine the problem of designing a mixed H2/H∞ controller which minimizes a quadratic H2 performance measure while satisfying a prescribed H∞-norm bound on the closed-loop system. It is established that sufficient conditions for the existence of the mixed H2/H∞ controller and the associated performance upper bound could be cast in the form of linear matrix inequalities.
    Journal of the Franklin Institute. 01/2008;
  • Jiqing Qiu, Ting Sun, Yan Shi
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    ABSTRACT: In this paper, we investigate the extension of classical complex measure and fuzzy measure -fuzzy complex measure, and show the conception of absolute continuity of fuzzy complex measure which is an improvement of the absolute continuity in [3], then we get a series of equivalent proposition, and give a metric space. At last, we define the auto continuity and property (P), and discuss the transmissibility of absolute continuity and property (P) on metric space. It will build the certain foundation for the intensive research of fuzzy complex analysis.
    01/2007;
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    ABSTRACT: Fuzzy reasoning is the very important process in the intelligent systems. Very few papers address the research for interpolative reasoning under multidimensional sparse rules. Moreover, these methods sometimes can not guarantee the convexity of result. Nowadays, multidimensional sparse rules base focus on the premises composed of many fuzzy sets, but do not consider the consequences composed of multidimensional fuzzy sets. Thus the fuzzy production rule can not express the complicate problems in the real world. It needs to be extended. This paper proposes a similarity relation between fuzzy sets. Based on the similarity relation, then we propose an improved fuzzy interpolative reasoning method. Moreover, we extend the method to the case of complex multidimensional consequences.
    Proceedings of the 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2007, July 30 - August 1, 2007, Qingdao, China; 01/2007
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    ABSTRACT: In this paper, we investigate the problem of robust stability for uncertain linear neutral systems with time-varying and distributed delays. The uncertainties considered in the paper are norm-bounded type. The time-varying delay function in this paper may be not continuously differentiable and its derivative may be not smaller than one. Based on a new Lyapunov-Krasovskii functional, a new delay-dependent stability criteria is derived, which is in terms of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness and the potential of the proposed techniques
    Control Conference, 2006. CCC 2006. Chinese; 01/2006
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    ABSTRACT: This paper investigates the problem of designing a robust output feedback controller for a class of uncertain Markovian jump nonlinear systems that guarantees the L<sub>2</sub>-gain from an exogenous input to a regulated output is less than or equal to a prescribed value. First, we approximate this class of uncertain Markovian jump nonlinear systems by a class of uncertain Takagi-Sugeno fuzzy models with Markovian jumps. Then, based on an LMI approach, LMIbascd sufficient conditions for the uncertain Markovian jump nonlinear systems to have an H<sub>∞</sub> performance are derived. An illustrative example is used to illustrate the effectiveness of the proposed design techniques.
    American Control Conference, 2005. Proceedings of the 2005; 07/2005
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    ABSTRACT: The paper addresses the problem of designing a robust filter for a class of uncertain Markovian jump nonlinear systems described by a class of uncertain Takagi-Sugeno fuzzy models with Markovian jumps. Based on an LMI approach, LMI-based sufficient conditions that guarantee the L<sub>2</sub>-from an exogenous input to an estimation error is less than a prescribed value are derived. A tunnel diode circuit is used to illustrate the effectiveness of the proposed design techniques.
    American Control Conference, 2005. Proceedings of the 2005; 07/2005
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    ABSTRACT: This paper presents a new fuzzy interpolative reasoning method in the sparse fuzzy rule bases based on so-called similarity relations of fuzzy sets. By this reasoning method, an inference consequence can be simply obtained, and is a normal and convex fuzzy set without any limitation, which shows the potential ability of the proposed method in real-world fuzzy applications.
    Hybrid Intelligent Systems, 2004. HIS '04. Fourth International Conference on; 01/2005
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    Shaocheng Tong, Yan Shi
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    ABSTRACT: The adaptive fuzzy control scheme based on observer is proposed for a class of MIMO nonlinear systems whose states are unavailable. By applying "dominant input" concept and combining adaptive control, H<sup>∞</sup> control with fuzzy logic systems, the output feedback control law and parameter adaptive law are derived. The whole control scheme can guarantee the stability of the closed-loop, and achieve H<sup>∞</sup> tracking performance.
    Fuzzy Systems, 2004. Proceedings. 2004 IEEE International Conference on; 08/2004
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    ABSTRACT: When fuvy rule base is sparse, reference (I) proposed a fuzzy interpolative-type reasoning based on Lagrange's interpolation. This fuzzy reasoning method can guarantee the membership function of the inference consequence to be of ~iamgular-fypeiiall ofmembership fyDEtiDllE dfuuy rules and an Observation are given by triangular-type when fuzzy rule base is sparse. But to many membership functions of other type, this method is not applicable. We generalized this method so that this method is applicable to most normal convex fuzzy sets.
    01/2004;
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    ABSTRACT: This paper considers the problem of robust guaranteed cost control of linear discrete time-delay systems with parametric uncertainties. By matrix inequality approach, the robust quadratic stability of the system is studied. A control design method is developed such that the closed-loop system with a cost function has a upper bound irrespective of all admissible parameter uncertainties and unknown time delays. Furthermore, the upper bound (cost) can be optimized by incorporating with a minimization problem. A numerical example is given to show the potential of the proposed techniques.
    Journal of Computational and Applied Mathematics 08/2003; · 0.99 Impact Factor
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    ABSTRACT: The stochastic stabilization and control for a class of linear time-delay systems via output feedback are considered. The jumping parameters are modelled as a continuous-time, discrete-state Markov process.
    IMA Journal of Mathematical Control and Information. 01/2003; 20(2).
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    ABSTRACT: Based on the fuzzy clustering method, we improved a neuro-fuzzy learning algorithm. In this improved approach, before learning fuzzy rules we extract typical data from training data by using fuzzy c-means clustering algorithm, in order to remove redundant data and resolve conflicts in data, and make them as practical training data. By these typical data, fuzzy rules can be tuned by using the neuro-fuzzy learning algorithm. Therefore, the learning time can be expected to be reduced and the fuzzy rules generated by the improved approach are reasonable and suitable for the identified system model. Moreover, the efficiency of the improved method is also shown by identifying nonlinear functions.
    Fuzzy Sets and Systems 01/2001; · 1.75 Impact Factor
  • Yan Shi, Peng Shi
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    ABSTRACT: This paper studies the problem of Kalman filtering for a class of uncertain linear continuous-time systems with Markovian jumping parameters. The system under consideration is subjected to time-varying norm-bounded parameter uncertainties in the state and measurement equations. Stochastic quadratic stability of the above system is analyzed. A state estimator is designed such that the covariance of the estimation error is guaranteed to be within a certain bound for all admissible uncertainties, which is in terms of solutions of two sets of coupled algebraic Riccati equations
    Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on; 02/2000
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    ABSTRACT: In this paper, we try to analyze several conventional neuro-fuzzy learning algorithms, which are widely used in recent fuzzy applications for tuning fuzzy rules, and give a summarization of their properties in detail. Some of these properties show that the uses of the conventional neuro-fuzzy learning algorithms are difficult or inconvenient sometimes for constructing an optimal fuzzy system model in practical fuzzy applications.
    Fuzzy Sets and Systems. 01/2000;
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    ABSTRACT: In this paper, we develop a new approach of neuro-fuzzy learning algorithm for tuning fuzzy rules by using training input–output data, based on the gradient descent method. A major advantage of this approach is that fuzzy rules or membership functions can be learned without changing the form of fuzzy rule table used in usual fuzzy applications, so that the case of non-firing or weak-firing can be well avoided, which is different from the conventional neuro-fuzzy learning algorithms. Moreover, some properties of the developed approach are also discussed. Finally, the efficiency of the developed approach is illustrated by means of identifying non-linear functions.
    Fuzzy Sets and Systems. 01/2000;
  • JACIII. 01/1999; 3:200-206.
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    ABSTRACT: This paper studies the problem of robust control of a class of uncertain bilinear continuous-time systems. The class of uncertain systems is described by a state space model with time-varying norm-bounded parameter uncertainty in the state equation. We address the problem of robust H ∞ control in which both robust stability and a prescribed H ∞ performance are required to be achieved irrespective of the uncertainties. Both state feedback and output feedback controllers are designed. It has been shown that the above problems can be recast into H ∞ syntheses for related bilinear systems without parameter uncertainty, which can be solved via a Riccati inequality approach. Two examples are given to show the potential of the proposed technique.
    Mathematical Problems in Engineering 01/1998; · 1.38 Impact Factor
  • The Fifth International Conference on Neural Information Processing, ICONIP'R98, Kitakyushu, Japan, October 21-23, 1998, Proceedings; 01/1998

Publication Stats

278 Citations
6.85 Total Impact Points

Institutions

  • 2000–2009
    • Kyushu Tokai University
      Kumamoto, Kumamoto Prefecture, Japan
  • 2008
    • King Fahd University of Petroleum and Minerals
      • Department of Systems Engineering
      Dhahran, Al Mintaqah ash Sharqiyah, Saudi Arabia
  • 2005
    • University of Auckland
      • Department of Electrical & Computer Engineering
      Auckland, Auckland, New Zealand
  • 1997–2001
    • Osaka Electro-Communication University
      Neyagawa, Ōsaka, Japan