Abstract
This paper is aimed at developing a finite-time adaptive control for non-strict feedback nonlinear systems with unknown backlash-like hysteresis. First, the adaptive fuzzy systems are applied to identify the unknown functions which contain all the system states. Second, based on the practical finite-time stability criteria, a novel finite-time adaptive switched gain controller via nonlinear command filter is proposed. The stability analysis shows that the tracking error converges to a small region around the origin within a finite time. Meanwhile, all the resulting closed-loop system states are bounded. Finally, simulation examples verify the effectiveness of the designed control scheme.
Similar content being viewed by others
References
Bhat, S.P., Bernstein, D.S.: Finite-time stability of continuous autonomous systems. SIAM J. Control Optim. 38(3), 751–766 (2000)
Chen, B., Liu, X.P., Ge, S.S., Lin, C.: Adaptive fuzzy control of a class of nonlinear systems by fuzzy approximation approach. IEEE Trans. Fuzzy Syst. 20(6), 1012–1021 (2012)
Dong, W., Farrell, J.A., Polycarpou, M.M., Djapic, V., Sharma, M.: Command filtered adaptive backstepping. IEEE Trans. Control Syst. Technol. 20(3), 566–580 (2011)
Huo, X., Ma, L., Zhao, X., Niu, B., Zong, G.: Observer-based adaptive fuzzy tracking control of MIMO switched nonlinear systems preceded by unknown backlash-like hysteresis. Inf. Sci. 490, 369–386 (2019)
Levant, A.: Higher-order sliding modes, differentiation and output-feedback control. Int. J. Control 76(9–10), 924–941 (2003)
Li, H., Wang, L., Du, H., Boulkroune, A.: Adaptive fuzzy backstepping tracking control for strict-feedback systems with input delay. IEEE Trans. Fuzzy Syst. 25(3), 642–652 (2016)
Li, J., Xia, Y., Qi, X., Gao, Z.: On the necessity, scheme, and basis of the linear-nonlinear switching in active disturbance rejection control. IEEE Trans. Ind. Electron. 64(2), 1425–1435 (2016)
Li, Y., Li, K., Tong, S.: Finite-time adaptive fuzzy output feedback dynamic surface control for MIMO nonstrict feedback systems. IEEE Trans. Fuzzy Syst. 27(1), 96–110 (2018)
Li, Y., Tong, S.: Command-filtered-based fuzzy adaptive control design for MIMO switched non-strict feedback nonlinear systems. IEEE Trans. Fuzzy Syst. 25(3), 668–681 (2016)
Li, Y., Tong, S., Li, T.: Composite adaptive fuzzy output feedback control design for uncertain nonlinear strict-feedback systems with input saturation. IEEE Trans. Cybern. 45(10), 2299–2308 (2014)
Li, Y.X.: Finite time command filtered adaptive fault tolerant control for a class of uncertain nonlinear systems. Automatica 106, 117–123 (2019)
Li, Z., Shan, J., Gabbert, U.: Inverse compensation of hysteresis using Krasnoselskii–Pokrovskii model. IEEE/ASME Trans. Mechatron. 23(2), 966–971 (2018)
Liu, X., Gu, G., Zhou, K.: Robust stabilization of MIMO nonlinear systems by backstepping. Automatica 35(5), 987–992 (1999)
Liu, Y., Li, J., Tong, S., Chen, C.P.: Neural network control based adaptive learning design for nonlinear systems with full-state constraints. IEEE Trans. Neural Netw. Learn. Syst. 27(7), 1562–1571 (2016)
Liu, Y., Liu, X., Jing, Y., Zhang, Z.: A novel finite-time adaptive fuzzy tracking control scheme for nonstrict feedback systems. IEEE Trans. Fuzzy Syst. 27(4), 646–658 (2018)
Liu, Y.J., Tong, S., Chen, C.P., Li, D.J.: Neural controller design-based adaptive control for nonlinear MIMO systems with unknown hysteresis inputs. IEEE Trans. Cybern. 46(1), 9–19 (2015)
Ma, H., Liang, H., Zhou, Q., Ahn, C.K.: Adaptive dynamic surface control design for uncertain nonlinear strict-feedback systems with unknown control direction and disturbances. IEEE Trans. Syst. Man Cybern. Syst. 49(3), 506–515 (2018)
Ma, L., Huo, X., Zhao, X., Niu, B., Zong, G.: Adaptive neural control for switched nonlinear systems with unknown backlash-like hysteresis and output dead-zone. Neurocomputing 357, 203–214 (2019)
Na, J., Ren, X., Herrmann, G., Qiao, Z.: Adaptive neural dynamic surface control for servo systems with unknown dead-zone. Control Eng. Pract. 19(11), 1328–1343 (2011)
Pan, Y., Wang, H., Li, X., Yu, H.: Adaptive command-filtered backstepping control of robot arms with compliant actuators. IEEE Trans. Control Syst. Technol. 26(3), 1149–1156 (2017)
Pelliciari, M., Marano, G.C., Cuoghi, T., Briseghella, B., Lavorato, D., Tarantino, A.M.: Parameter identification of degrading and pinched hysteretic systems using a modified Bouc–Wen model. Struct. Infrastruct. Eng. 14(12), 1573–1585 (2018)
Shen, Q., Jiang, B., Cocquempot, V.: Adaptive fuzzy observer-based active fault-tolerant dynamic surface control for a class of nonlinear systems with actuator faults. IEEE Trans. Fuzzy Syst. 22(2), 338–349 (2013)
Su, C.Y., Stepanenko, Y., Svoboda, J., Leung, T.P.: Robust adaptive control of a class of nonlinear systems with unknown backlash-like hysteresis. IEEE Trans. Autom. Control 45(12), 2427–2432 (2000)
Tan, X., Baras, J.S.: Modeling and control of hysteresis in magnetostrictive actuators. Automatica 40(9), 1469–1480 (2004)
Tong, S., Min, X., Li, Y.: Observer-based adaptive fuzzy tracking control for strict-feedback nonlinear systems with unknown control gain functions. IEEE Trans. Cybern. (2020). https://doi.org/10.1109/TCYB.2020.2977175
Tong, S., Sun, K., Sui, S.: Observer-based adaptive fuzzy decentralized optimal control design for strict-feedback nonlinear large-scale systems. IEEE Trans. Fuzzy Syst. 26(2), 569–584 (2017)
Wang, F., Chen, B., Liu, X., Lin, C.: Finite-time adaptive fuzzy tracking control design for nonlinear systems. IEEE Trans. Fuzzy Syst. 26(3), 1207–1216 (2017)
Wang, F., Chen, B., Sun, Y., Lin, C.: Finite time control of switched stochastic nonlinear systems. Fuzzy Sets Syst. 365, 140–152 (2019)
Wang, H., Chen, B., Lin, C.: Approximation-based adaptive fuzzy control for a class of non-strict-feedback stochastic nonlinear systems. Sci. China Inf. Sci. 57(3), 1–16 (2014)
Wang, H., Liu, P.X., Zhao, X., Liu, X.: Adaptive fuzzy finite-time control of nonlinear systems with actuator faults. IEEE Trans. Cybern. (2019). https://doi.org/10.1109/TCYB.2019.2902868
Wang, H., Liu, S., Yang, X.: Adaptive neural control for non-strict-feedback nonlinear systems with input delay. Inf. Sci. 514, 605–616 (2017)
Wang, L., Li, H., Zhou, Q., Lu, R.: Adaptive fuzzy control for nonstrict feedback systems with unmodeled dynamics and fuzzy dead zone via output feedback. IEEE Trans. Cybern. 47(9), 2400–2412 (2017)
Wang, L., Mendel, J.M.: Fuzzy basis functions, universal approximation, and orthogonal least-squares learning. IEEE Trans. Neural Netw. 3(5), 807–814 (1992)
Xia, J., Zhang, J., Sun, W., Zhang, B., Wang, Z.: Finite-time adaptive fuzzy control for nonlinear systems with full state constraints. IEEE Trans. Syst. Man Cybern. Syst. 49(7), 1541–1548 (2018)
Yu, J., Shi, P., Dong, W., Yu, H.: Observer and command-filter-based adaptive fuzzy output feedback control of uncertain nonlinear systems. IEEE Trans. Ind. Electron. 62(9), 5962–5970 (2015)
Yu, J., Shi, P., Zhao, L.: Finite-time command filtered backstepping control for a class of nonlinear systems. Automatica 92, 173–180 (2018)
Yu, J., Zhao, L., Yu, H., Lin, C., Dong, W.: Fuzzy finite-time command filtered control of nonlinear systems with input saturation. IEEE Trans. Cybern. 48(8), 2378–2387 (2017)
Zhou, J., Wen, C., Yang, G.: Adaptive backstepping stabilization of nonlinear uncertain systems with quantized input signal. IEEE Trans. Autom. Control 59(2), 460–464 (2013)
Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 61973198), the Research Fund for the Taishan Scholar Project of Shandong Province of China and SDUST Research Fund (No. 2015TDJH105).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Wei, W., Zhang, W. Finite-time adaptive switched gain control for non-strict feedback nonlinear systems via nonlinear command filter. Nonlinear Dyn 100, 3485–3496 (2020). https://doi.org/10.1007/s11071-020-05693-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11071-020-05693-5