170
Views
1
CrossRef citations to date
0
Altmetric
Articles

Adaptive fuzzy asymptotic control design for MIMO nonlinear systems with state constraints

, , &
Pages 610-623 | Received 10 Sep 2021, Accepted 19 Oct 2022, Published online: 21 Nov 2022

References

  • Chang, M. F. (2018). A novel dynamic proportional-type iterative learning control design for non-linear systems. Journal of Control and Decision, 5(3), 265–276. https://doi.org/10.1080/23307706.2017.1353933
  • Chen, B., & Liu, X. P. (2005). Fuzzy approximate disturbance decoupling of MIMO nonlinear systems by backstepping and application to chemical processes. IEEE Transactions on Fuzzy Systems, 13(6), 832–847. https://doi.org/10.1109/TFUZZ.2005.859322
  • Chen, B., Liu, X. P., Liu, K. F., & Lin, C. (2009a). Direct adaptive fuzzy control of nonlinear strict-feedback systems. Automatica, 45(6), 1530–1535. https://doi.org/10.1016/j.automatica.2009.02.025
  • Chen, B., Liu, X. P., Liu, K. F., & Lin, C. (2009b). Novel adaptive neural control design for nonlinear MIMO time-delay systems. Automatica, 45(6), 1554–1560. https://doi.org/10.1016/j.automatica.2009.02.021
  • Chen, M., Ge, S. S., & How, B. V. E. (2010). Robust adaptive neural network control for a class of uncertain MIMO nonlinear systems with input nonlinearities. IEEE Transactions on Neural Networks, 21(5), 796–812. https://doi.org/10.1109/TNN.2010.2042611
  • Dong, G. W., Cao, L., Yao, D. Y., Li, H. Y., & Lu, R. Q. (2021). Adaptive attitude control for multi-MUAVs with output dead-zone and actuator fault. IEEE/CAA Journal of Automatica Sinica, 8(9), 1567–1575. https://doi.org/10.1109/JAS.2020.1003605
  • Ge, S. S., & Wang, C. (2004). Adaptive neural control of uncertain MIMO nonlinear systems. IEEE Transactions on Neural Networks, 15(3), 674–692. https://doi.org/10.1109/TNN.2004.826130
  • He, W., Kong, L. H., Dong, Y. T., Yu, Y., Yang, C. G., & Sun, C. Y. (2019). Fuzzy tracking control for a class of uncertain MIMO nonlinear systems with state constraints. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(3), 543–554. https://doi.org/10.1109/TSMC.6221021
  • Li, D., D. J. Li, Liu, Y. J., Tong, S. C., & Chen, C. L. P. (2017). Approximation-based adaptive neural tracking control of nonlinear MIMO unknown time-varying delay systems with full state constraints. IEEE Transactions on Cybernetics, 47(10), 3100–3109. https://doi.org/10.1109/TCYB.2017.2707178
  • Li, D. J., Lu, S. M., Liu, Y. J., & Li, D. P. (2017). Adaptive fuzzy tracking control based barrier functions of uncertain nonlinear MIMO systems with full-state constraints and applications to chemical process. IEEE Transactions on Fuzzy Systems, 26(4), 2145–2159. https://doi.org/10.1109/TFUZZ.91
  • Li, H. Y., Wu, Y., & Chen, M. (2021). Adaptive fault-tolerant tracking control for discrete-time multiagent systems via reinforcement learning algorithm. IEEE Transactions on Cybernetics, 51(3), 1163–1174. https://doi.org/10.1109/TCYB.6221036
  • Li, Y. X. (2020). Barrier Lyapunov function-based adaptive asymptotic tracking of nonlinear systems with unknown virtual control coefficients. Automatica, 121, 1–9.https://doi.org/10.1016/j.automatica.2020.109181
  • Li, Y. X., Hu, X. Y., Che, W. W., & Hou, Z. S. (2021). Event-based adaptive fuzzy asymptotic tracking control of uncertain nonlinear systems. IEEE Transactions on Cybernetics, 29(10), 3003–3013.
  • Li, Y. X., & Yang, G. H. (2016). Adaptive asymptotic tracking control of uncertain nonlinear systems with input quantization and actuator faults. Automatica, 72, 177–185. https://doi.org/10.1016/j.automatica.2016.06.008
  • Liu, L., Liu, Y. J., Chen, A. Q., Tong, S. C., & Chen, C. L. P. (2020). Integral Barrier Lyapunov function-based adaptive control for switched nonlinear systems. Science China Information Sciences, 63(3), 132203:1–132203:14.
  • Liu, W., Ma, Q., Lu, J. W., Yuan, X. S., & Zhuang, G. M. (2019). A neural composite dynamic surface control for pure-feedback systems with unknown control gain signs and full state constraints. International Journal of Robust and Nonlinear Control, 29(16), 5720–5743. https://doi.org/10.1002/rnc.v29.16
  • Liu, Y. C., & Zhu, Q. D. (2022). Adaptive neural network asymptotic control design for MIMO nonlinear systems based on event-triggered mechanism. Information Sciences, 603, 91–105. https://doi.org/10.1016/j.ins.2022.04.048
  • Liu, Y. C., Zhu, Q. D., & Fan, X. (2022). Event-triggered adaptive fuzzy control for stochastic nonlinear time-delay systems. Fuzzy Sets and Systems, https://doi.org/10.1016/j.fss.2022.07.005 .
  • Liu, Y. H., Su, C. Y., & Li, H. Y. (2021). Adaptive output feedback funnel control of uncertain nonlinear systems with arbitrary relative degree. IEEE Transactions on Automatic Control, 66(6), 2854–2860. https://doi.org/10.1109/TAC.2020.3012027
  • Liu, Y. J., & Tong, S. C. (2017). Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems. Automatica, 76, 143–152. https://doi.org/10.1016/j.automatica.2016.10.011
  • Liu, Y. J., Tong, S. C., & Li, T. S. (2011). Observer-based adaptive fuzzy tracking control for a class of uncertain nonlinear MIMO systems. Fuzzy Sets and Systems, 164(1), 25–44. https://doi.org/10.1016/j.fss.2010.09.002
  • Peng, S., Wang, Q. Z., & Fu, B. Z. (2022). Exponential stabilization of chaotic systems based on fuzzy time-triggered intermittent control. Chaos, Solitons & Fractals, 162(112390), 1–9.
  • Qiu, J. B., Sun, K. K., Rudas, I. J., & Gao, H. J. (2020). Command filter-based adaptive NN control for MIMO nonlinear systems with full-state constraints and actuator hysteresis. IEEE Transactions on Cybernetics, 50(7), 2905–2915. https://doi.org/10.1109/TCYB.6221036
  • Shahnazi, R. (2015). Output feedback adaptive fuzzy control of uncertain MIMO nonlinear systems with unknown input nonlinearities. ISA Transactions, 54, 39–51. https://doi.org/10.1016/j.isatra.2014.07.006
  • Slotine, J. J., & Li, W. P. (1991). Applied nonlinear control. Prentice-Hall.
  • Sun, G. F., Li, D. W., & Ren, X. M. (2015). Modified neural dynamic surface approach to output feedback of MIMO nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, 26(2), 224–236. https://doi.org/10.1109/TNNLS.2014.2312001
  • Tee, K. P., Ge, S. S., & Tay, E. H. (2009). Barrier Lyapunov functions for the control of output-constrained nonlinear systems. Automatica, 45(4), 918–927. https://doi.org/10.1016/j.automatica.2008.11.017
  • Tong, S. C., Li, Y. M., Feng, G., & Li, T. S. (2011). Observer-based adaptive fuzzy backstepping dynamic surface control for a class of MIMO nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 41(4), 1124–1135. https://doi.org/10.1109/TSMCB.2011.2108283
  • Tong, S. C., Min, X., & Li, Y. X. (2020). Observer-based adaptive fuzzy tracking control for strict-feedback nonlinear systems with unknown control gain functions. IEEE Transactions on Cybernetics, 50(9), 3903–3913. https://doi.org/10.1109/TCYB.6221036
  • Wang, D., Cheng, L., & Jun, Y. (2021). Self-learning robust control synthesis and trajectory tracking of uncertain dynamics. IEEE Transactions on Cybernetics, 52(1), 278–286. https://doi.org/10.1109/TCYB.2020.2979694
  • Wang, W., Long, J., Wen, C. Y., & Huang, J. S. (2019). Recent advances in distributed adaptive consensus control of uncertain nonlinear multi-agent systems. Journal of Control and Decision, 7(1), 1–20.
  • Wang, X. J., Niu, B., Zhai, L., Kong, J., & Wang, X. M. (2022). A novel distributed bipartite consensus control of nonlinear multiagent systems via prioritized strategy approach. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(6), 2852–2856.
  • Wen, G. X., Chen, C. L. P., & Ge, S. S. (2021). Simplified optimized backstepping control for a class of nonlinear strict-feedback systems with unknown dynamic functions. IEEE Transactions on Cybernetics, 51(9), 4567–4580. https://doi.org/10.1109/TCYB.2020.3002108
  • Wen, G. X., Li, B., & Niu, B. (2022). Optimized backstepping control using reinforcement learning of observer-critic-actor architecture based on fuzzy system for a class of nonlinear strict-feedback systems. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/TFUZZ.2022.3148865
  • Zhang, C. L., Yang, J., & Wen, C. Y. (2016). Global stabilisation for a class of uncertain non-linear systems: a novel non-recursive design framework. Journal of Control and Decision, 4(2), 57–69. https://doi.org/10.1080/23307706.2016.1263164
  • Zhang, L., Zong, G. D., Zhao, X. D., & Zhao, N. (2022). Real-time reachable set control for singular Markov jump networked cascade systems. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(3), 1124–1128.
  • Zhang, Z. Q., Xu, S. Y., & Zhang, B. Y. (2014). Asymptotic tracking control of uncertain nonlinear systems with unknown actuator nonlinearity. IEEE Transactions on Automatic Control, 59(5), 1336–1341. https://doi.org/10.1109/TAC.2013.2289704
  • Zhao, N., Shi, P., Xing, W., & Jonathon, C. (2021). Observer-based event-triggered approach for stochastic networked control systems under denial of service attacks. IEEE Transactions on Control of Network Systems, 8(1), 158–167. https://doi.org/10.1109/TCNS.6509490
  • Zhou, J., Wen, C. Y., & Zhang, Y. (2006). Adaptive output control of nonlinear systems with uncertain dead-zone nonlinearity. IEEE Transactions on Automatic Control, 51(3), 504–511. https://doi.org/10.1109/TAC.2005.864200
  • Zhu, Q. D., Liu, Y. C., & Wen, G. X. (2020). Adaptive neural network output feedback control for stochastic nonlinear systems with full state constraints. ISA Transactions, 101, 60–68. https://doi.org/10.1016/j.isatra.2020.01.021
  • Zong, G. D., Sun, H. B., & Nguang, S. K. (2022). Decentralized adaptive neuro-output feedback saturated control for INS and its application to AUV. IEEE Transactions on Neural Networks and Learning Systems, 32(12), 5492–5501. https://doi.org/10.1109/TNNLS.2021.3050992

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.