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Observer-Based Stabilization Control of Time-Delay T-S Fuzzy Systems via the Non-Uniform Delay Partitioning Approach

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Abstract

It is well known that intelligent control technology plays an important role in the design of many control systems, and intelligent control has aroused wide attention from scholars. Fuzzy control is also the case because fuzzy control is one branch of intelligent control. The Takagi-Sugeno (T-S) fuzzy model is an effective approach when dealing with complex nonlinear systems, and the advantages of fuzzy controller design is that the linear control methods can be used. In addition, nonlinearity and time delay are inherent and not all states are available in many practical system. Therefore, the observer-based stabilization control for time-delay T-S fuzzy systems is of great significance. With the help of the non-uniform delay partitioning approach, a novel method is put forward to analyze the stability of the time-delay T-S fuzzy system and design the observer-based feedback controller via the parallel distributed compensation (PDC) scheme. The sufficient conditions of asymptotic stability for both nominal and uncertain time-delay T-S fuzzy system are derived based on the Lyapunov stability theory and linear matrix inequality (LMI) techniques. What is more, the solving methods to obtain the controller gain matrices, observer gain matrices, and upper bound of time delay are presented. Two illustrative examples are given to demonstrate the effectiveness and verify the superiority of our developed methods. From the simulation results, it can be found that the most prominent advantages of our proposed methods lie on larger delay bound and less decision variables compared with other related methods. The problem of observer-based stabilization control for continuous nonlinear time-delay systems is investigated in this paper, and the delay-dependent stability criteria are derived to achieve greater delay bound by virtual of the non-uniform delay partitioning approach. Numerical examples further confirmed the effectiveness and advantages of our developed methods.

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References

  1. Zhang D. Matlab Fuzzy system design. Beijing: National Defence Industry Press; 2009.

    Google Scholar 

  2. Liu J. Intelligent control. Beijing: Electronic Industry Press; 2012.

    Google Scholar 

  3. Shamim Kaiser M, Chowdhury ZI, AI Mamun S, Hussain A, Mahmud M. A neuro-fuzzy control system based on feature extraction of surface electromyogram signal for solar-powered wheelchair. Cong Comput 2016;8:946–954.

    Google Scholar 

  4. Czubenko M, Kowalczuk Z, Ordys A. Autonomous driver based on an intelligent system of decision-making. Cong Comput 2015;7:569–581.

    Google Scholar 

  5. Qiu J, Feng G, Gao H. Static-output-feedback H control of continuous-time T-S fuzzy affine systems via piecewise Lyapunov functions. IEEE Trans Fuzzy Syst 2013;21(2):245–261.

    Article  Google Scholar 

  6. Su X, Shi P, Wu L, Song Y. A novel control design on discrete-time Takagi-Sugeno fuzzy systems with time-varying delays. IEEE Trans Fuzzy Syst 2013;21(4):655–671.

    Article  Google Scholar 

  7. Dou C, Zhang X, Guo S, Mao C. Delay-independent excitation control for uncertain large power systems using wide-area measurement signals. Electrical power and energy systems 2010;32:210–217.

    Article  Google Scholar 

  8. Dou C, Duan X, Jia X, Niu P. Study of delay-independent decentralized guaranteed cost control for large-scale systems. Int J Control Autom Syst 2011;9(3):478–488.

    Article  Google Scholar 

  9. Huijiao W, Peng S, Jianhua Z. Event-triggered fuzzy filtering for a class of nonlinear networked control systems. Sig Process 2015;113:159–168.

    Article  Google Scholar 

  10. Minglai C, Li J. Non-fragile guaranteed cost control for Takagi-Sugeno fuzzy hyperbolic systems. International Journal Of System Science 2015;46(9):1614–1627.

    Article  Google Scholar 

  11. Qi Z, Di L, Gao Y, Lam H-k, Sakthived R. Interval type-2 fuzzy control for nonlinear discrete-time systems with time-varying delays. Neurocomputing 2015;157:22–32.

    Article  Google Scholar 

  12. Kim SH. Improved approach to robust H stabilization of discrete-time T-S fuzzy systems with time-varying delays. IEEE Trans Fuzzy Syst 2010;18(5):1008–1015.

    Article  Google Scholar 

  13. Zhu X-L, Chen B, Yue D, Wang Y. An improved input delay approach to stabilization of fuzzy systems under variable sampling. IEEE Trans Fuzzy Syst 2012;20(2):330–341.

    Article  Google Scholar 

  14. Wang C, Shen Y. Robust H control for stochastic systems with nonlinearity, uncertainty and time-varying delay. Computers and Mathematics with Applications 2012;63:985–998.

    Article  CAS  Google Scholar 

  15. Xianghui Z, Wuneng Z, Jun Y. A novel scheme for synchronization control of stochastic neural networks with multiple time-varying delays. Neurocomputing 2015;159:50–57.

    Article  Google Scholar 

  16. Sun J, Liu GP, Chen J. Improved delay-range-dependent stability criteria for linear systems with time-varying delays. Automatica 2010;46:466–470.

    Article  Google Scholar 

  17. Yan H, Wang T, Zhang H, Shi H. Event-triggered H control for uncertain networked T-S fuzzy systems with time delay. Neurocomputing 2015;157:273–279.

    Article  Google Scholar 

  18. Gao J, Su H, Ji X-F, Chu J. New delay-dependent absolute stability criteria for Lurie control systems. Acta Automatica Sinica 2008;34(10):1275–1280.

    Article  Google Scholar 

  19. An J, Wen G. Improved stability criteria for time-varying delayed T-S fuzzy systems via delay partitioning approach. IEEE Fuzzy Sets and Syst 2011;185(1):83–94.

    Article  Google Scholar 

  20. Parlakci MNA. Delay-dependent stability criteria for interval time-varying delay systems with nonuniform delay partitioning approach. Turk J Electr Eng Comput Sci 2015;19(5):763–773.

    Google Scholar 

  21. Du B, Lam J, Shu Z, Wang Z. A delay-partitioning projection approach to stability analysis of continuous systems with multiple delay components. IET Control Theory and Applications 2009;3(4):383–390.

    Article  Google Scholar 

  22. Wang C, Shen Y. Delay partitioning approach to robust stability analysis for uncertain stochastic systems with interval time-varying delay. IET Control Theory Appl 2012;6(7):875–883.

    Article  Google Scholar 

  23. Zhao Y, Gao H, Lam J, Du B. Stability and stabilization of delayed T-S fuzzy systems: a delay partitioning approach. IEEE Trans Fuzzy Syst 2009;17(4):750–761.

    Article  Google Scholar 

  24. Lin C, Wang QG, Lee TH, He Y. Design of observer-based H control for fuzzy time-delay systems. IEEE Trans Fuzzy Syst 2008;16(10):534–543.

    Google Scholar 

  25. Shuai S, Shaocheng T, Li Y. Observer-based fuzzy adaptive prescribed performance tracking control for nonlinear stochastic systems with input saturation. Neurocomputing 2015;158:100–108.

    Article  Google Scholar 

  26. Gassara H, El Hajjaji A, Chaabane M. Observer-based robust H reliable control for uncertain T-S fuzzy systems with state time delay. IEEE Trans Fuzzy Syst 2010;18(6):1027–1040.

    Article  Google Scholar 

  27. Lin C, Wang QG, Lee TH, He Y, Chen. B. Observer-based H control for T-S fuzzy systems with time delay: delay-dependent design method. IEEE Trans Syst Man Cybern B 2007;37(4):1030–1038.

    Article  Google Scholar 

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Acknowledgments

The authors express their sincere gratitude to the reviewers for their constructive suggestions which help improve the presentation of this paper. This work is supported by the National Science Foundation of China under Grants 61403425 and 61473314.

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Correspondence to Miaoping Sun.

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Nian, X., Sun, M., Guo, H. et al. Observer-Based Stabilization Control of Time-Delay T-S Fuzzy Systems via the Non-Uniform Delay Partitioning Approach. Cogn Comput 9, 225–236 (2017). https://doi.org/10.1007/s12559-017-9448-6

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