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Command-Filtered Adaptive Fuzzy Control for Switched MIMO Nonlinear Systems with Unknown Dead Zones and Full State Constraints

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Abstract

This paper studies the problem of adaptive fuzzy control for switched multi-input and multi-output (MIMO) nonlinear systems with full state constraints and unknown dead zones. First, fuzzy logic systems (FLSs) serve as approximate instruments of unknown nonlinear functions, which are used to tackle the issue of parameter uncertainties. The unmeasured states are estimated by designing a switched MIMO state observer. Then, an adaptive fuzzy control strategy based on the command filter technique and average dwell time (ADT) method is proposed, which tackles the issue of “explosion of complexity” in the conventional backstepping recursive procedure, and also overcomes the drawback of dynamic surface control by designing compensating signals. Furthermore, the dead zone nonlinearities are handled using the information for dead zone slopes. In particular, barrier Lyapunov functions are employed to testify the stability of the system under our proposed control signals while preventing the constraint violations. Finally, two simulation examples demonstrate the availability and effectiveness of the presented adaptive controller.

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References

  1. Zhou, J., Wen, C., Zhang, Y.: Adaptive backstepping control of a class of uncertain nonlinear systems with unknown backlash-like hysteresis. IEEE Trans. Autom. Control 49(10), 1751–1759 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  2. Li, Y., Niu, B., Zong, G., Zhao, J., Zhao, X.: Command filter-based adaptive neural finite-time control for stochastic nonlinear systems with time-varying full state constraints and asymmetric input saturation. Int. J. Syst. Sci. 53(1), 199–221 (2022)

  3. Chen, M., Ge, S.S., Ren, B.: Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints. Automatica 47(3), 452–465 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  4. Li, Y., Tong, S., Li, T.: Adaptive fuzzy output-feedback control for output constrained nonlinear systems in the presence of input saturation. Fuzzy Sets Syst. 248, 138–155 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  5. Wang, H., Bai, W., Liu, P.X.: Finite-time adaptive fault-tolerant control for nonlinear systems with multiple faults. IEEE/CAA J. Autom. Sin. 6(6), 1417–1427 (2019)

    Article  MathSciNet  Google Scholar 

  6. Chang, Y., Zhou, P., Niu, B., Wang, H., Xu, N., Alassafi, M. O., Ahmad, A. M.: Switched-observer-based adaptive output-feedback control design with unknown gain for pure-feedback switched nonlinear systems via average dwell time. Int. J. Syst. Sci. 52(9):1731–1745 (2021)

  7. Swaroop, D., Hedrick, J.K., Yip, P.P., Gerdes, J.C.: Dynamic surface control for a class of nonlinear systems. IEEE Trans. Autom. Control 45(10), 1893–1899 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  8. Chang, X.-H., Park, J.H., Shi, P.: Fuzzy resilient energy-to-peak filtering for continuous-time nonlinear systems. IEEE Trans. Fuzzy Syst. 25(6), 1576–1588 (2017)

    Article  Google Scholar 

  9. Liu, S., Zhang, L., Niu, B., Zhao, X., Ahmad, A.: Adaptive neural finite-time hierarchical sliding mode control of uncertain under-actuated switched nonlinear systems with backlash-like hysteresis. Inform. Sci. 599, 147–169 (2022)

  10. Peng, J., Dubay, R.: Adaptive fuzzy backstepping control for a class of uncertain nonlinear strict-feedback systems based on dynamic surface control approach. Expert Syst. Appl. 120, 239–252 (2019)

    Article  Google Scholar 

  11. Li, Y., Xu, N., Niu, B., Chang, Y., Zhao, J., Zhao, X.: Small-gain technique-based adaptive fuzzy command filtered control for uncertain nonlinear systems with unmodeled dynamics and disturbances. Int. J. Adapt. Control Signal Process. 35(9), 1664–1684 (2021)

    Article  MathSciNet  Google Scholar 

  12. Cui, G., Yu, J., Wang, Q.-G.: Finite-time adaptive fuzzy control for MIMO nonlinear systems with input saturation via improved command-filtered backstepping. IEEE Trans. Syst. Man Cybern. 52(2), 980–989 (2022)

    Article  Google Scholar 

  13. Chen, Z., Niu, B., Zhang, L., Zhao, J., Ahmad, A.: Command filtering-based adaptive neural network control for uncertain switched nonlinear systems using event-triggered communication. Int. J. Robust Nonlinear Control 32(11), 6507–6522 (2022)

  14. Xue, G., Lin, F., Li, S., Liu, H.: Composite learning control of uncertain fractional-order nonlinear systems with actuator faults based on command filtering and fuzzy approximation. Int. J. Fuzzy Syst. (2022). https://doi.org/10.1007/s40815-021-01242-3

    Article  Google Scholar 

  15. Wang, Y., Xu, N., Liu, Y., Zhao, X.: Adaptive fault-tolerant control for switched nonlinear systems based on command filter technique. Appl. Math. Comput. 392, 125725 (2021)

    MathSciNet  MATH  Google Scholar 

  16. Zhang, H., Wang, H., Niu, B., Zhang, L., Ahmad, A.M.: Sliding-mode surface-based adaptive actor-critic optimal control for switched nonlinear systems with average dwell time. Inf. Sci. 580, 756–774 (2021)

    Article  MathSciNet  Google Scholar 

  17. Zhang, L., Zong, G., Zhao, X., Zhao, N.: Real-time reachable set control for singular Markov jump networked cascade systems. IEEE Trans. Circuits Syst. II 69(3), 1124–1128 (2022)

    Article  Google Scholar 

  18. Zhang, H., Xu, N., Zong, G., Alkhateeb, A.F.: Adaptive fuzzy hierarchical sliding mode control of uncertain under-actuated switched nonlinear systems with actuator faults. Int. J. Syst. Sci. 52(8), 1499–1514 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  19. Tang, F., Niu, B., Wang, H., Zhang, L., Zhao, X.: Adaptive fuzzy tracking control of switched MIMO nonlinear systems with full state constraints and unknown control directions. IEEE Trans. Circuits Syst. II 69(6), 2912–2916 (2022)

    Article  Google Scholar 

  20. Ma, R., Zhao, J.: Backstepping design for global stabilization of switched nonlinear systems in lower triangular form under arbitrary switchings. Automatica 46(11), 1819–1823 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  21. Niu, B., Zhao, J.: Tracking control for output-constrained nonlinear switched systems with a barrier Lyapunov function. Int. J. Syst. Sci. 44(4–6), 978–985 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  22. Cai, J., Mei, C., Yan, Q.: Semi-global adaptive backstepping control for parametric strict-feedback systems with non-triangular structural uncertainties, ISA Trans. 126, 180–189 (2022)

  23. Lai, G., Liu, Z., Zhang, Y., Philip Chen, C.L., Xie, S.: Adaptive backstepping-based tracking control of a class of uncertain switched nonlinear systems. Automatica 91, 301–310 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  24. Long, L., Zhao, J.: Adaptive output-feedback neural control of switched uncertain nonlinear systems with average dwell time. IEEE Trans. Neural Netw. Learn. Syst. 26(7), 1350–1362 (2015)

    Article  MathSciNet  Google Scholar 

  25. Niu, B., Liu, Y., Zong, G., Han, Z., Fu, J.: Command filter-based adaptive neural tracking controller design for uncertain switched nonlinear output-constrained systems. IEEE Trans. Cybern. 47(10), 3160–3171 (2017)

    Article  Google Scholar 

  26. Ma, L., Huo, X., Zhao, X., Zong, G.: Adaptive fuzzy tracking control for a class of uncertain switched nonlinear systems with multiple constraints: a small-gain approach. Int. J. Fuzzy Syst. 21(8), 2609–2624 (2019)

    Article  MathSciNet  Google Scholar 

  27. Cui, Y., Zhang, H., Wang, Y., Jiang, H.: A fuzzy adaptive tracking control for MIMO switched uncertain nonlinear systems in strict-feedback form. IEEE Trans. Fuzzy Syst. 27(12), 2443–2452 (2019)

    Article  Google Scholar 

  28. Ha, S., Liu, H., Li, S., Liu, A.: Backstepping-based adaptive fuzzy synchronization control for a class of fractional-order chaotic systems with input saturation. Int. J. Fuzzy Syst. 21(5), 1571–1584 (2019)

    Article  MathSciNet  Google Scholar 

  29. Juang, C.-F., Lai, M.-G., Zeng, W.-T.: Evolutionary fuzzy control and navigation for two wheeled robots cooperatively carrying an object in unknown environments. IEEE Trans. Cybern. 45(9), 1731–1743 (2014)

    Article  Google Scholar 

  30. Diao, S., Sun, W., Wang, L., Wu, J.: Finite-time adaptive fuzzy control for nonlinear systems with unknown backlash-like hysteresis. Int. J. Fuzzy Syst. 23(7), 2037–2047 (2021)

    Article  Google Scholar 

  31. Tao, G., Kokotovic, P.V.: Adaptive control of plants with unknown dead-zones. IEEE Trans. Autom. Control 39(1), 59–68 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  32. Jing, Z.: Decentralized adaptive control for large-scale time-delay systems with dead-zone input. Automatica 44(7), 1790–1799 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  33. Zhang, T.P., Ge, S.S.: Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form. Automatica 44(7), 1895–1903 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  34. Yu, J., Shi, P., Dong, W., Lin, C.: Adaptive fuzzy control of nonlinear systems with unknown dead zones based on command filtering. IEEE Trans. Fuzzy Syst. 26(1), 46–55 (2018)

    Article  Google Scholar 

  35. Tong, S., Li, Y.: Adaptive fuzzy output feedback control of MIMO nonlinear systems with unknown dead-zone inputs. IEEE Trans. Fuzzy Syst. 21(1), 134–146 (2013)

    Article  Google Scholar 

  36. Ma, L., Huo, X., Zhao, X., Zong, G.D.: Observer-based adaptive neural tracking control for output-constrained switched MIMO nonstrict-feedback nonlinear systems with unknown dead zone. Nonlinear Dyn. 99(2), 1019–1036 (2020)

    Article  MATH  Google Scholar 

  37. Tee, K.P., Ge, S.S., Tay, E.H.: Barrier Lyapunov functions for the control of output-constrained nonlinear systems. Automatica 45(4), 918–927 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  38. Tang, Z.L., Ge, S.S., Tee, K.P., He, W.: Robust adaptive neural tracking control for a class of perturbed uncertain nonlinear systems with state constraints. IEEE Trans. Syst. Man Cybern. 46(12), 1618–1629 (2016)

    Article  Google Scholar 

  39. Wu, J., Su, B., Li, J., Zhang, X., Li, X., Chen, W.: Adaptive fuzzy control for full states constrained systems with nonstrict-feedback form and unknown nonlinear dead zone. Inf. Sci. 376, 233–247 (2017)

    Article  MATH  Google Scholar 

  40. Li, D.P., Li, D.J., Liu, Y.J., Tong, S., Chen, C.L.P.: Approximation-based adaptive neural tracking control of nonlinear MIMO unknown time-varying delay systems with full state constraints. IEEE Trans. Cybern. 47(10), 3100–3109 (2017)

    Article  Google Scholar 

  41. Yu, J., Zhao, L., Yu, H., Lin, C.: Barrier Lyapunov functions-based command filtered output feedback control for full-state constrained nonlinear systems. Automatica 105, 71–79 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  42. Zhang, Q., Zhai, D., Dong, J.: Observer-based adaptive fuzzy decentralized control of uncertain large-scale nonlinear systems with full state constraints. Int. J. Fuzzy Syst. 21(4), 1085–1103 (2019)

    Article  MathSciNet  Google Scholar 

  43. Sun, W., Yuan, W., Shao, Y., Sun, Z., Zhao, J., Sun, Q.: Adaptive fuzzy control of strict-feedback nonlinear time-delay systems with full-state constraints. Int. J. Fuzzy Syst. 20(8), 2556–2565 (2018)

    Article  MathSciNet  Google Scholar 

  44. Lian, Y., Xia, J., Yang, W., Wang, X., Wang, L.: Adaptive fuzzy tracking control for stochastic nonlinear systems with nonstrict-feedback and dead zone. Int. J. Fuzzy Syst. 23(7), 2324–2334 (2021)

    Article  Google Scholar 

  45. Precup, R.-E., Preitl, S.: PI-fuzzy controllers for integral plants to ensure robust stability. Inf. Sci. 177(20), 4410–4429 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  46. Chen, T., Babanin, A., Muhammad, A., Chapron, B., Chen, C.: Modified evolved bat algorithm of fuzzy optimal control for complex nonlinear systems. Rom. J. Inf. Sci. Technol. 23, 28–40 (2020)

    Google Scholar 

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Acknowledgements

This work was partially supported by the National Natural Science Foundation of China (62203064) and the Education Committee Liaoning Province, China (LJ2019002).

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Authors and Affiliations

  1. College of Control Science and Engineering, Bohai University, Jinzhou, 121013, Liaoning, China

    Youqian He, Xiao-Heng Chang & Xudong Zhao

  2. College of Mathematical Sciences, Bohai University, Jinzhou, 121013, Liaoning, China

    Huanqing Wang

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Correspondence to Xudong Zhao.

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He, Y., Chang, XH., Wang, H. et al. Command-Filtered Adaptive Fuzzy Control for Switched MIMO Nonlinear Systems with Unknown Dead Zones and Full State Constraints. Int. J. Fuzzy Syst. 25, 544–560 (2023). https://doi.org/10.1007/s40815-022-01384-y

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