Command-filter-based finite-time event-triggered adaptive output feedback control for nonlinear systems with state-function constraints. (English) Zbl 1530.93445
Summary: This paper investigates the finite-time (FT) adaptive output feedback control for a class of nonlinear systems with asymmetric state-function constraints and unknown external disturbances. Incorporating the asymmetric barrier Lyapunov function (BLF) into the backstepping technique, a new control approach is proposed to ensure that all states do not cross the constraint boundary. With the help of the command filter, the explosion of complexity induced by repeated differentiations of virtual controllers is eliminated, and the corresponding compensation system is used to offset the filter error. Meanwhile, the fuzzy logic system (FLS) and fuzzy state observer are employed to approximate unknown nonlinear functions and estimate unmeasurable states respectively. For effectively conserve communication resources, a novel adaptive event-triggered controller is proposed such that all signals of the closed-loop system are bounded, the tracking error converges to a small neighborhood containing the origin in finite time. Finally, the feasibility of the fabricated control scheme is verified with two examples.
MSC:
| 93D40 | Finite-time stability |
| 93C40 | Adaptive control/observation systems |
| 93B52 | Feedback control |
| 93C10 | Nonlinear systems in control theory |
| 93E11 | Filtering in stochastic control theory |
| 93C42 | Fuzzy control/observation systems |
References:
| [1] | Cheng, L.; Wang, Z.; Jiang, F.; Li, J., Adaptive neural network control of nonlinear systems with unknown dynamics. Adv. Space Res., 1114-1123 (2021) |
| [2] | Xu, K.; Wang, H.; Liu, P., Adaptive fuzzy finite-time tracking control of nonlinear systems with unmodeled dynamics. Appl. Math. Comput. (2023) · Zbl 07701077 |
| [3] | Yu, D.; Yang, M.; Liu, Y.; Wang, Z.; Chen, C., Adaptive fuzzy tracking control for uncertain nonlinear systems with multiple actuators and sensors faults. IEEE T. Fuzzy Syst., 1, 104-116 (2023) |
| [4] | Liu, L.; Li, Z.; Chen, Y.; Wang, R., Disturbance observer-based adaptive intelligent control of marine vessel with position and heading constraint condition related to desired output. IEEE T. Neur. Net. Lear. (2023) |
| [5] | Chao, D.; Qi, R.; Jiang, B., Adaptive fault-tolerant control for the ascent phase of hypersonic vehicle with time-varying full state constraints. Aerosp. Sci. Technol. (2022) |
| [6] | Li, D.; Wang, Y.; Liu, Y.; Liu, L., IBLFs-based adaptive fuzzy control for continuous stirred tank reactors with full state constraints and actuator faults. J. Process Control, 14-24 (2023) |
| [7] | Chen, T.; Zhu, M.; Zheng, Z., Adaptive path following control of a stratospheric airship with full-state constraint and actuator saturation. Aerosp. Sci. Technol. (2019) |
| [8] | Liu, Y.; Zhao, W.; Liu, L.; Li, D.; Tong, S.; Chen, C., Adaptive neural network control for a class of nonlinear systems with function constraints on states. IEEE T. Neur. Net. Lear., 6, 2732-2741 (2023) |
| [9] | Li, D.; Han, H.; Qiao, J., Adaptive NN controller of nonlinear state-dependent constrained systems with unknown control direction. IEEE T. Neur. Net. Lear. (2023) |
| [10] | Yu, T.; Liu, Y.; Liu, L.; Tong, S., Adaptive fuzzy control of nonlinear systems with function constraints based on time-varying IBLFs. IEEE T. Fuzzy Syst., 11, 4939-4952 (2022) |
| [11] | S. Zhou, Tracking control of uncertain robotic systems with function constraints on states, in: CCC, 2022, pp. 593-598. |
| [12] | S. Zhou, X. Wang, Robust adaptive control for nonlinear strict-feedback systems with function constraints on states, in: CCDC, 2022, pp. 5172-5177. |
| [13] | Gao, T.; Li, T.; Liu, Y.; Tong, S.; Sun, F., Observer-based adaptive fuzzy control of non-strict feedback nonlinear systems with function constraints. IEEE T. Fuzzy Syst., 8, 2556-2567 (2023) |
| [14] | Swaroop, D.; Hedrick, J.; Yip, P.; Gerdes, J., Dynamic surface control for a class of nonlinear systems. IEEE T. Automat. Contr., 10, 1893-1899 (2000) · Zbl 0991.93041 |
| [15] | Tang, L.; Yang, M.; Liu, Y.; Tong, S., Adaptive output feedback fuzzy fault-tolerant control for nonlinear full-state-constrained switched systems. IEEE T. Cybern., 4, 2325-2334 (2023) |
| [16] | Tong, S.; Li, Y.; Li, Y.; Liu, Y., Observer-based adaptive fuzzy backstepping control for a class of stochastic nonlinear strict-feedback systems. IEEE T. Syst. Man Cy. B., 6, 1693-1704 (2011) |
| [17] | Zhang, H.; Liu, Y.; Wang, Y., Observer-based finite-time adaptive fuzzy control for nontriangular nonlinear systems with full-state constraints. IEEE T. Cybern., 3, 1110-1120 (2021) |
| [18] | Wang, L.; Liu, P.; Wang, H., Fast finite-time control for nonaffine stochastic nonlinear systems against multiple actuator constraints via output feedback. IEEE T. Cybern., 5, 3253-3262 (2023) |
| [19] | 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. Internat. J. Systems Sci., 199-221 (2021) · Zbl 1483.93553 |
| [20] | Wei, W.; Zhang, W., Command-filter-based adaptive fuzzy finite-time output feedback control for state-constrained nonlinear systems with input saturation. IEEE T. Fuzzy Syst., 10, 4044-4056 (2022) |
| [21] | Cui, G.; Yu, J.; Shi, P., Observer-based finite-time adaptive fuzzy control with prescribed performance for nonstrict-feedback nonlinear systems. IEEE T. Fuzzy Syst., 3, 767-778 (2022) |
| [22] | Yu; Cheng, S.; Shi, P.; Lin, C., Command-filtered neuroadaptive output-feedback control for stochastic nonlinear systems with input constraint. IEEE T. Cybern., 4, 2301-2310 (2023) |
| [23] | Si, C.; Wang, Q.; Yu, J., Event-triggered adaptive fuzzy neural network output feedback control for constrained stochastic nonlinear systems. IEEE T. Neur. Net. Lear. (2023) |
| [24] | Wang, M.; Wang, L., Finite-time performance guaranteed event-triggered adaptive control for nonlinear systems with unknown control direction. J. Franklin Inst., 2463-2486 (2022) · Zbl 1485.93364 |
| [25] | Liu, Y.; Zhang, H.; Wang, Y.; Ren, H.; Li, Q., Adaptive fuzzy prescribed finite-time tracking control for nonlinear system with unknown control directions. IEEE T. Fuzzy Syst., 6, 1993-2003 (2022) |
| [26] | Min, H.; Xu, S.; Zhang, Z., Adaptive finite-time stabilization of stochastic nonlinear systems subject to full-state constraints and input saturation. IEEE T. Automat. Contr., 3, 1306-1313 (2021) · Zbl 1536.93707 |
| [27] | Song, Z.; Li, P.; Sun, Z.; Wang, Z., Finite-time adaptive fuzzy event-triggered control of constrained nonlinear systems via bounded command filter. IEEE T. Fuzzy Syst., 1, 117-128 (2023) |
| [28] | Zhao, L.; Liu, G.; Yu, J., Finite-time adaptive fuzzy tracking control for a class of nonlinear systems with full-state constraints. IEEE T. Fuzzy Syst., 8, 2246-2255 (2021) |
| [29] | Bhat, S.; Bernstein, D., Finite-time stability of continuous autonomous systems. SIAM J. Control Optim., 3, 751-766 (2000) · Zbl 0945.34039 |
| [30] | Liu, L.; Li, X.; Liu, Y.; Tong, S., Neural network based adaptive event trigger control for a class of electromagnetic suspension systems. Control Eng. Pract. (2021) |
| [31] | Levant, A., Higher-order sliding modes, differentiation and output-feedback control. Int. J. Control., 76, 924-941 (2003) · Zbl 1049.93014 |
| [32] | Qian, C.; Du, H., Global output feedback stabilization of a class of nonlinear systems via linear sampled-data control. IEEE T. Automat. Contr., 11, 2934-2939 (2012) · Zbl 1369.93503 |
| [33] | Li, Y., Command filter adaptive asymptotic tracking of uncertain nonlinear systems with time-varying parameters and disturbances. IEEE T. Automat. Contr., 6, 2973-2980 (2022) · Zbl 1537.93404 |
| [34] | Niu, B.; Liu, Y.; Zhou, W.; Li, H.; Duan, P.; Li, J., Multiple Lyapunov functions for adaptive neural tracking control of switched nonlinear nonlower-triangular systems. IEEE T. Cybern., 5, 1877-1886 (2020) |
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.
