105
Views
0
CrossRef citations to date
0
Altmetric
Research Articles

Finite-time adaptive optimal control of uncertain strict-feedback nonlinear systems based on fuzzy observer and reinforcement learning

, , , & ORCID Icon
Pages 1553-1570 | Received 09 Oct 2023, Accepted 28 Jan 2024, Published online: 08 Feb 2024

References

  • Bellman, R. E. (1957). Dynamic programming princeton university press princeton.  New Jersey Google Scholar, 24–73.
  • Berstekas, D. P. (1995). Dynamic programming and optimal control. Athena scientific.
  • Chen, F., Jiang , R., & Zhang, K. (2016). Robust Backstepping Sliding-Mode Control and Observer-Based Fault Estimation for a Quadrotor UAV. IEEE Transactions on Industrial Electronics, 63(8), 5044–5056.
  • Chen, X., Sun, J., & Wang, Y. (2020). Finite-time control for attitude tracking of spacecraft with actuator faults. Robotics, 10(4), 128.
  • Cui, D., Ahn, C. K., & Xiang, Z. (2023). Fault-tolerant fuzzy observer-based fixed-time tracking control for nonlinear switched systems. IEEE Transactions on Fuzzy Systems, 31(12), 4410–4420. https://doi.org/10.1109/TFUZZ.2023.3284917
  • Cui, D., Niu, B., Wang, H., & Yang, D. (2019). Adaptive fuzzy output-feedback fault-tolerant tracking control of a class of uncertain nonlinear switched systems. International Journal of Systems Science, 50(14), 2673–2686. https://doi.org/10.1080/00207721.2019.1672119
  • Dong, H., Cao, J., & Liu, H. (2023). Observers-based event-triggered adaptive fuzzy backstepping synchronization of uncertain fractional order chaotic systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 33(4), Article 043113. https://doi.org/10.1063/5.0135758
  • Feng, Y., Chen, Y., & Li, X. (2019). Adaptive fuzzy observer-based robust control for a class of uncertain nonholonomic mobile robots. IEEE Transactions on Fuzzy Systems, 27(10), 1982–1995.
  • Gao, W., & Jiang, Z. P. (2018). Learning-based adaptive optimal tracking control of strict-feedback nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, 29(99), 2614–2624. https://doi.org/10.1109/TNNLS.2017.2761718
  • Huang, H., & Lewis, F. L. (2020). Adaptive dynamic programming for discrete-time nonlinear optimal control: An overview. IEEE Transactions on Cybernetics, 50(5), 1869–1881. https://doi.org/10.1109/TCYB.6221036
  • Huang, X., Lin, W., & Yang, B. (2005). Global finite-time stabilization of a class of uncertain nonlinear systems. Automatica, 41(5), 881–888. https://doi.org/10.1016/j.automatica.2004.11.036
  • Li, B.B.H, & Gong, W. (2020). Extended state observer-based finite-time dynamic surface control for trajectory tracking of a quadrotor unmanned aerial vehicle. Transactions of the Institute of Measurement and Control, 42(15), 2956–2968.
  • Li, G. W. 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, 30(10), 4322–4335. https://doi.org/10.1109/TFUZZ.2022.3146981
  • Li, H., & Wang, Y. (2019). Newton method for optimal control problems governed by semilinear parabolic equations. Journal of Optimization Theory and Applications, 182(1), 141–163.
  • Li, J., Zhang, Y., & Chen, W. (2019). Fuzzy observer-based reinforcement learning control for a class of unknown nonlinear systems. IEEE Transactions on Fuzzy Systems, 27(10), 2059–2070. https://doi.org/10.1109/TFUZZ.91
  • Li, X., & Zhang, Y. (2019). Fuzzy q-learning: A reinforcement learning algorithm for fuzzy logic systems. IEEE Transactions on Fuzzy Systems, 28(12), 3056–3067.
  • Li, Y., & Li, Y. (2020). Optimal control of discrete-time nonlinear systems using deep reinforcement learning. IEEE Transactions on Neural Networks and Learning Systems, 31(4), 1217–1229.
  • Li, Y., Zhang, J., Liu, W., & Tong, S. (2022). Observer-based adaptive optimized control for stochastic nonlinear systems with input and state constraints. IEEE Transactions on Neural Networks and Learning Systems, 33(12), 7791–7805. doi:10.1109/TNNLS.2021.3087796
  • Liu, Y. J., & Tong, S. (2016). Barrier Lyapunov functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints. Automatica, 64(C), 70–75. https://doi.org/10.1016/j.automatica.2015.10.034
  • Ma, Z., & Ma, H. (2018). Adaptive finite-time dynamic output-feedback FTC design for mimo nonlinear systems with actuator and sensor faults. IEEE Access, 6, 1–1. https://doi.org/10.1109/ACCESS.2018.2812929
  • Modares, H., Lewis, F. L., & Sistani, N. (2014). Integral reinforcement learning and experience replay for adaptive optimal control of partially-unknown constrained-input continuous-time systems – sciencedirect. Automatica, 50(1), 193–202. https://doi.org/10.1016/j.automatica.2013.09.043
  • Pontryagin, L. S., Boltyanskii, V. G., Gamkrelidze, R. V., & Mishchenko, E. F. (1962). The mathematical theory of optimal processes. Interscience.
  • Sun, Y., Gao, C., Wu, L. B., & Yang, Y. H. (2023). Fuzzy observer-based command filtered tracking control for uncertain strict-feedback nonlinear systems with sensor faults and event-triggered technology. Nonlinear Dynamics, 103(4), 1–17.
  • Tian, Y., Liu, Y., & Zhang, X. (2020). Finite-time control for robotic manipulators. IEEE Transactions on Industrial Electronics, 67(8), 7097–7106.
  • 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 B, 41(4), 1124–1135. https://doi.org/10.1109/TSMCB.2011.2108283
  • Wang, F., Chen, B., Liu, X., & Lin, C. (2018). Finite-time adaptive fuzzy tracking control design for nonlinear systems. IEEE Transactions on Fuzzy Systems, 26(3), 1207–1216. https://doi.org/10.1109/TFUZZ.91
  • Wang, H., Song, W., Liang, Y., Li, Q., & Liang, D. (2022). Observer-based finite frequency h state-feedback control for autonomous ground vehicles. ISA Transactions, 121(4), 75–85. https://doi.org/10.1016/j.isatra.2021.03.027
  • Wang, H., Zhang, T., Zhang, X., & Li, Q. (2023). Observer-based path tracking controller design for autonomous ground vehicles with input saturation. CAA Journal of Automatica Sinica, 10(3), 749–761. https://doi.org/10.1109/JAS.2023.123078
  • Wang, W., & Li, H. (2018). Fuzzy reinforcement learning for adaptive traffic signal control. IEEE Transactions on Intelligent Transportation Systems, 19(3), 765–775. https://doi.org/10.1109/TITS.2017.2706963
  • Wang, Y. L. X., & Zhang, Y. (2021). Finite-time consensus control of multi-agent systems with input saturation and external disturbances. International Journal of Robust and Nonlinear Control, 31(1), 149–168.
  • Wen, G., Chen, C. L. P., Feng, J., & Zhou, N. (2018). Optimized multi-agent formation control based on an identifier-actor-critic reinforcement learning algorithm. IEEE Transactions on Fuzzy Systems, 26(5), 2719–2731. https://doi.org/10.1109/TFUZZ.2017.2787561
  • Wen, G., Chen, C. L. P., Ge, S. S., Yang, H., & Liu, X. (2019). Optimized adaptive nonlinear tracking control using actor-critic reinforcement learning strategy. IEEE Transactions on Industrial Informatics, 15(9), 4969–4977. https://doi.org/10.1109/TII.9424
  • Wu, J., He, F., Shen, H., Ding, S., & Wu, Z. G. (2023). Adaptive NN fixed-time fault-tolerant control for uncertain stochastic system with deferred output constraint via self-triggered mechanism. IEEE Transactions on Cybernetics, 53(9), 5892–5903. https://doi.org/10.1109/TCYB.2022.3205765
  • Wu, J., Wang, W., Shihong, D., Xiangpeng, X., & Yi, Y. (2023). Adaptive neural optimized control for uncertain strict-feedback systems with unknown control directions and pre-set performance. Communications in Nonlinear Science and Numerical Simulation, 126, Article 107506.
  • Wu, X., He, X., & Wu, L. (2020). Finite-time adaptive fault-tolerant control for a class of nonlinear systems with actuator faults. Journal of Control, Automation and Electrical Systems, 31(5), 1075–1086. https://doi.org/10.1007/s40313-020-00618-4
  • Yang, Y. L. T., & Tong, S. (2020). Adaptive neural networks finite-time optimal control for a class of nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, 31(11), 4451–4460. https://doi.org/10.1109/TNNLS.5962385
  • Yu, Q., He, X., Wu, L., Guo, L., & Hu, Y. (2021). Finite-time adaptive event-triggered fault-tolerant control of nonlinear systems based on fuzzy observer. Information Sciences, 572(3), 241–262. https://doi.org/10.1016/j.ins.2021.04.097
  • Zha, W., Zhai, J., Fei, S., & Wang, Y. (2014). Finite-time stabilization for a class of stochastic nonlinear systems via output feedback. ISA Transactions, 53(3), 709–716. https://doi.org/10.1016/j.isatra.2014.01.005
  • Zhang, S., & Wu, Y. (2021). On the convergence of stochastic gradient descent with random initialization for non-convex optimization. IEEE Transactions on Information Theory, 67(2), 1378–1390.
  • Zhang, W., & Li, T. (2022). Adaptive fuzzy observer-based tracking control for underactuated USVs. IEEE Transactions on Fuzzy Systems, 30(1), 136–146.
  • Zhang, Y., Hao, Y., & Wang, S. (2021). Finite-time control of spacecraft with uncertain disturbances based on adaptive sliding mode control. Robotics, 10(4), 128. https://doi.org/10.3390/robotics10040128
  • Zhang, Y., Wang, X., & Wu, X. (2021). Fuzzy observer-based adaptive trajectory tracking control for a quadrotor uav. Aerospace Science and Technology, 115, Article 106172. https://doi.org/10.1016/j.ast.2021.106815
  • Zhu, Y. L. Q., & Wen, G. (2022). Adaptive tracking control for perturbed strict-feedback nonlinear systems based on optimized backstepping technique. IEEE Transactions on Neural Networks and Learning Systems, 32(5), 853–865.

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.