Research article

Finite-time fuzzy output-feedback control for $ p $-norm stochastic nonlinear systems with output constraints

  • Received: 06 September 2020 Accepted: 19 November 2020 Published: 11 December 2020
  • MSC : 37F15, 34D09

  • This paper investigates the finite-time control problem of $ p $-norm stochastic nonlinear systems subject to output constraint. Combining a tan-type barrier Lyapunov function (BLF) with the adding a power integrator technique, a fuzzy state-feedback controller is constructed. Then, an output-feedback controller design scheme is developed by the constructed state-feedback controller and a reduce-order observer. Finally, both the rigorous analysis and the simulation results demonstrate that the designed output-feedback controller not only guarantees that the output constraint is not violated, but also ensures that the system is semi-global finite-time stable in probability (SGFSP).

    Citation: Liandi Fang, Li Ma, Shihong Ding. Finite-time fuzzy output-feedback control for $ p $-norm stochastic nonlinear systems with output constraints[J]. AIMS Mathematics, 2021, 6(3): 2244-2267. doi: 10.3934/math.2021136

    Related Papers:

  • This paper investigates the finite-time control problem of $ p $-norm stochastic nonlinear systems subject to output constraint. Combining a tan-type barrier Lyapunov function (BLF) with the adding a power integrator technique, a fuzzy state-feedback controller is constructed. Then, an output-feedback controller design scheme is developed by the constructed state-feedback controller and a reduce-order observer. Finally, both the rigorous analysis and the simulation results demonstrate that the designed output-feedback controller not only guarantees that the output constraint is not violated, but also ensures that the system is semi-global finite-time stable in probability (SGFSP).



    加载中


    [1] S. Y. Khoo, J. L. Yin, Z. Man, X. Yu, Finite-time stabilization of stochastic nonlinear systems in strict-feedback form, Automatica, 47 (2013), 1403–1410.
    [2] S. H. Ding, W. H. Chen, K. Q. Mei, D. Murray-Smith, Disturbance observer design for nonlinear systems represented by input-output models, IEEE Trans. Ind. Electron, 67 (2020), 1222–1232.
    [3] X. D. Li, X. Y. Yang, T. W. Huang, Persistence of delayed cooperative models: Impulsive control method, Appl. Math. Comput., 342 (2019), 130–146.
    [4] H. Shen, M. S. Chen, Z. G. Wu, J. D. Cao, J. H. Park, Reliable event-triggered asynchronous passive control for semi-Markov jump fuzzy systems and its application, IEEE T. Fuzzy Syst., 28 (2020), 1708–1722.
    [5] S. H. Ding, A. Levant, S. H. Li, Simple homogeneous sliding-mode controller, Automatica, 67 (2016), 22–32. doi: 10.1016/j.automatica.2016.01.017
    [6] X. Y. Yang, X. D. Li, Q. Xi, P. Y. Duan, Review of stability and stabilization for impulsive delayed systems, Math. Biosci. Eng., 15 (2018), 1495–1515. doi: 10.3934/mbe.2018069
    [7] S. H. Ding, S. H. Li, Second-order sliding mode controller design subject to mismatched term, Automatica, 77 (2017), 388–392. doi: 10.1016/j.automatica.2016.07.038
    [8] K. Q. Mei, S. H. Ding, Second-order sliding mode controller design subject to an upper-triangular structure, IEEE T. Syst. Man Cybern. Syst., (2018), 1–11.
    [9] S. C. Tong, Y. M. Li, Observer-based adaptive fuzzy backstepping control of uncertain nonlinear pure-feedback systems, Sci. China Inform. Sci., 57 (2014), 1–14.
    [10] J. T. Hu, G. X. Sui, X. X. Lv, X. D. Li, Fixed-time control of delayed neural networks with impulsive perturbations, Nonlinear Anal. Model. Control, 23 (2018), 904–920. doi: 10.15388/NA.2018.6.6
    [11] X. D. Zhao, X. Y. Wang, L. Ma, G. D. Zong, Fuzzy approximation based asymptotic tracking control for a class of uncertain switched nonlinear systems, IEEE T. Fuzzy Syst., 28 (2020), 632–644. doi: 10.1109/TFUZZ.2019.2912138
    [12] F. Wang, B. Chen, Y. Sun, Y. Gao, C. Lin, Finite-time fuzzy control of stochastic nonlinear systems, IEEE T. Syst. Man Cybern., 50 (2020), 2617–2626.
    [13] L. Liu, W. Zheng, S. H. Ding, An adaptive SOSM controller design by using a sliding-mode-based filter and its application to buck converter, IEEE T. Circ. Syst. I., 67 (2020), 2409–2418.
    [14] H. Y. Li, Y. Wu, M. Chen, Adaptive fault-tolerant tracking control for discrete-time multi-agent systems via reinforcement learning algorithm, IEEE T. Syst. Man Cybern., (2020), 1–12.
    [15] Q. Zhou, W. Wang, H. Liang, M. Basin, B. Wang, Observer-based event-triggered fuzzy adaptive bipartite containment control of multi-agent systems with input quantization, IEEE T. Fuzzy Syst., (2019), 1–1.
    [16] Z. F. Li, T. S. Li, G. Feng, R. Zhao, Q. H. Shan, Neural network-based adaptive control for purefeedback stochastic nonlinear systems with time-varying delays and dead-zone input, IEEE T. Syst. Man Cybern. Syst., 50 (2020), 5317–5329. doi: 10.1109/TSMC.2018.2872421
    [17] S. Sui, C. L. P. Chen, S. C. Tong, Fuzzy adaptive finite-time control design for non-triangular stochastic nonlinear systems, IEEE T. Fuzzy Syst., 27 (2019), 172–184. doi: 10.1109/TFUZZ.2018.2882167
    [18] B. Niu, Y. J. Liu, W. L. Zhou, H. T. Li, P. Y. Duan, J. Q. Li, Multiple Lyapunov functions for adaptive neural tracking control of switched nonlinear nonlower-triangular systems, IEEE T. Cybernetics, 50 (2020), 1877–1886. doi: 10.1109/TCYB.2019.2906372
    [19] Y. M. Li, S. C. Tong, T. S. Li, Observer-based adaptive fuzzy tracking control of MIMO stochastic nonlinear systems with unknown control directions and unknown dead zones, IEEE T. Fuzzy Syst., 23 (2015), 1228–1241. doi: 10.1109/TFUZZ.2014.2348017
    [20] X. D. Li, J. H. Shen, R. Rakkiyappan, Persistent impulsive effects on stability of functional differential equations with finite or infinite delay, Appl. Math. Comput., 329 (2018), 14–22.
    [21] J. H. Park, H. Shen, X. H. Chang, T. H. Lee, Recent advances in control and filtering of dynamic systems with constrained signals, Switzerland: Springer, 2019.
    [22] L. D. Fang, L. Ma, S. H. Ding, J. H. Park, Finite-time stabilization of high-order stochastic nonlinear systems with asymmetric output constraints, IEEE T. Syst. Man Cybern. Syst., (2020), 1–13.
    [23] C. C. Chen, A unified approach to finite-time stabilization of high-order nonlinear systems with and without an output constraint, Int. J. Robust Nonlin. Control, 29 (2019), 393–407. doi: 10.1002/rnc.4393
    [24] S. H. Ding, J. H. Park, C. C. Chen, Second-order sliding mode controller design with output constraint, Automatica, 112 (2020), 108704. doi: 10.1016/j.automatica.2019.108704
    [25] L. B. Wu, J. H. Park, Adaptive fault-tolerant control of uncertain switched nonaffine nonlinear systems with actuator faults and time delays, IEEE T. Syst., Man, Cybern., Syst., 50 (2020), 3470–3480. doi: 10.1109/TSMC.2019.2894750
    [26] X. Jin, Adaptive fault tolerant tracking control for a class of stochastic nonlinear systems with output constraint and actuator faults, Syst. Control Lett., 107 (2017), 100–109. doi: 10.1016/j.sysconle.2017.07.007
    [27] S. H. Ding, K. Q. Mei, S. H. Li, A new second-order sliding mode and its application to nonlinear constrained systems, IEEE T. Automat. Contr., 64 (2019), 2545–2552. doi: 10.1109/TAC.2018.2867163
    [28] Y. M. Li, S. C. Tong, Adaptive fuzzy output constrained control design for multi-input multioutput stochastic nonstrict-feedback nonlinear systems, IEEE T. Syst. Man Cybern., 47 (2017), 4086– 4095.
    [29] B. Niu, W. Ding, H. Li, X. Xie, A novel neural-network-based adaptive control scheme for outputconstrained stochastic switched nonlinear systems, IEEE T. Syst. Man Cybern. Syst., 49 (2017), 418–432.
    [30] S. Yin, H. Yu, R. Shahnazi, A. Haghani, Fuzzy adaptive tracking control of constrained nonlinear switched stochastic pure-feedback systems, IEEE T. Syst. Man Cybern., 47 (2017), 579–588.
    [31] Q. K. Hou, S. H. Ding, X. H. Yu, Composite super-twisting sliding mode control design for PMSM speed regulation problem based on a novel disturbance observer, IEEE T. Energy Conver., (2020), 1–1.
    [32] D. Yang, X. D. Li, J. L. Qiu, Output tracking control of delayed switched systems via statedependent switching and dynamic output feedback, Nonlinear Anal. Hybri. Syst., 32 (2019), 294–305. doi: 10.1016/j.nahs.2019.01.006
    [33] H. Wang, Q. Zhu, Finite-time stabilization of high-order stochastic nonlinear systems in strictfeedback form, Automatica, 54 (2015), 284–291. doi: 10.1016/j.automatica.2015.02.016
    [34] W. T. Zha, J. Y. Zhai, S. M. Fei, Output feedback control for a class of stochastic high-order nonlinear systems with time-varying delays, Int. J. Robust Nonlin. Control, 24 (2015), 2243–2260.
    [35] H. Wang, Q. Zhu, Global stabilization of stochastic nonlinear systems via C1 and C controllers, IEEE T. Automat. Contr., 62 (2017), 5880–5887. doi: 10.1109/TAC.2016.2644379
    [36] W. Q. Li, X. J. Xie, S. Y. Zhang, Output-feedback stabilization of stochastic high-order nonlinear systems under weaker conditions, SIAM J. Control Optim., 49 (2011), 1262–1282. doi: 10.1137/100798259
    [37] M. Jiang, X. Xie, K. Zhang, Finite-time stabilization of stochastic high-order nonlinear systems with FT-SISS inverse dynamics, IEEE T. Automat. Contr., 64 (2019), 313–320. doi: 10.1109/TAC.2018.2827993
    [38] W. J. Si, X. D. Dong, F. F. Yang, Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics, Neural Netw., 99 (2018), 123–133. doi: 10.1016/j.neunet.2017.12.013
    [39] N. Duan, H. F. Min, Decentralized adaptive NN state-feedback control for large-scale stochastic high-order nonlinear systems, Neurocomputing, 173 (2016), 1412–1421. doi: 10.1016/j.neucom.2015.09.013
    [40] X. D. Zhao, X. Y. Wang, G. D. Zong, X. L. Zheng, Adaptive neural tracking control for switched high-order stochastic nonlinear systems, IEEE T. Syst. Man Cybern., 47 (2017), 3088–3099.
    [41] L. D. Fang, L. Ma, S. H. Ding, D. A. Zhao, Finite-time stabilization for a class of high-order stochastic nonlinear systems with an output constraint, Appl. Math. Comput., 358 (2019), 63–79.
    [42] C. C. Chen, Z. Y. Sun, A unified approach to finite-time stabilization of high-order nonlinear systems with an asymmetric output constraint, Automatica, 111 (2020), 108581. doi: 10.1016/j.automatica.2019.108581
    [43] L. D. Fang, L. Ma, S. H. Ding, D. A. Zhao, Robust finit-time stabilization of a class of high-order stochastic nonlinear systems subject to output constraint and disturbances, Int. J. Robust Nonlin. Control, 29 (2019), 5550–5573. doi: 10.1002/rnc.4685
    [44] C. C. Chen, Z. Y. Sun, Output feedback finite-time stabilization for high-order planar systems with an output constraint, Automatica, 114 (2020), 108843. doi: 10.1016/j.automatica.2020.108843
    [45] Y. Wu, X. J. Xie, Adaptive fuzzy control for high-order nonlinear time-delay systems with full-state constraints and input saturation, IEEE T. Fuzzy Syst., 28 (2020), 1652–1663. doi: 10.1109/TFUZZ.2019.2920808
    [46] L. D. Fang, S. H. Ding, J. H. Park, L. Ma, Adaptive fuzzy control for stochastic high-order nonlinear systems with output constraints, IEEE T. Fuzzy Syst., (2020), 1–1.
    [47] W. Sun, S. F. Su, G. W. Dong, W. W. Bai, Reduced adaptive fuzzy tracking control for highorder stochastic nonstrict feedback nonlinear system with full-state constraints, IEEE T. Syst. Man Cybern. Syst., (2019), 1–11.
    [48] L. D. Fang, H. S. Ding, J. H. Park, L. Ma, Adaptive Fuzzy Control for Nontriangular Stochastic High-Order Nonlinear Systems Subject to Asymmetric Output Constraints, IEEE T. Cybernetics, (2020), 1–12.
    [49] L. X. Wang, Adaptive fuzzy systems and control, Englewood Cliffs, NJ: PTR Prentice Hall, 1994.
  • Reader Comments
  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1376) PDF downloads(48) Cited by(5)

Article outline

Figures and Tables

Figures(4)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog