×

Command-filter-based adaptive finite-time consensus control for nonlinear strict-feedback multi-agent systems with dynamic leader. (English) Zbl 1530.93510

Summary: An adaptive finite-time consensus control method is investigated for nonlinear strict-feedback multi-agent systems that contain unknown parameters and a dynamic leader with both input and output. By using command filters, the “explosion of complexity” phenomenon in traditional backstepping technique can be avoided. The filter errors can be compensated by introducing compensating signals. Adaptive finite-time controllers are constructed by a backstepping technique, command filters, and compensating signals. In addition, the consensus performance and stability of closed-loop systems can be guaranteed in finite time basd on a practical finite-time stability criterion. Finally, a simulation example demonstrates the feasibility and effectiveness of the proposed adaptive finite-time consensus control method.

MSC:

93E11 Filtering in stochastic control theory
93C40 Adaptive control/observation systems
93D40 Finite-time stability
93D50 Consensus
93A16 Multi-agent systems
93C10 Nonlinear systems in control theory
93B52 Feedback control
Full Text: DOI

References:

[1] M. Chen, S.S. Ge, B.V.E. How, Y.S. Choo, Robust adaptive position mooring control for marine vessels, IEEE Trans. Control Syst. Technol. 21 (2) (2013) 395-409.
[2] S. Mehraeen, S. Jagannathan, M.L. Crow, Power system stabilization using adaptive neural network-based dynamic surface control, IEEE Trans. Power Syst. 26 (2) (2011) 669-680.
[3] Ye, D.; Yang, G. H., Adaptive fault-tolerant tracking control against actuator faults with application to flight control, IEEE Trans. Control Syst. Technol., 14, 6, 1088-1096 (2006)
[4] Lapierre, L.; Jouvencel, B., Robust nonlinear path-following control of an AUV, IEEE J. Oceanic Eng., 33, 2, 89-102 (2008)
[5] Refsnes, J. E.; Srensen, A. J.; Pettersen, K. Y., Model-based output feedback control of slender-body underactuated AUVs: theory and experiments, IEEE Trans. Control Syst. Technol., 16, 5, 930-946 (2008)
[6] Wen, C. Y.; Soh, Y. C., Decentralized adaptive control using integrator backstepping, Automatica, 33, 9, 1719-1724 (1997) · Zbl 1422.93104
[7] S.C. Tong, X. Min, Y.X. Li, Observer-based adaptive fuzzy tracking control for strict-feedback nonlinear systems with unknown control gain functions, IEEE Trans. Cybern. doi10.1109/TCYB.2020.2977175, 2020.
[8] Jankovic, M., Adaptive nonlinear output feedback tracking with a partial high-gain observer and backstepping, IEEE Trans. Autom. Control, 42, 1, 106-113 (1997) · Zbl 0872.93043
[9] Liu, C. G.; Wang, H. Q.; Liu, X. P.; Zhou, Y. C.; Lu, S. Y., Adaptive prescribed performance tracking control for strict-feedback nonlinear systems with zero dynamics, Int. J. Robust Nonlinear Control, 29, 18, 6507-6521 (2019) · Zbl 1447.93173
[10] Li, Y. M.; Li, K. W.; Tong, S. C., Finite-time adaptive fuzzy output feedback dynamic surface control for MIMO non-strict feedback systems, IEEE Trans. Fuzzy Syst., 27, 1, 96-110 (2019)
[11] Q.T. Yin, M. Wang, H. Jing, Stabilizing backstepping controller design for arbitrarily switched complex nonlinear system, Appl. Math. Comput. doi:10.1016/j.amc.2019.124789. · Zbl 1433.93053
[12] Guo, Q.; Zhang, Y.; Branko, G., Neural adaptive backstepping control of a robotic manipulator with prescribed performance constraint, IEEE Trans. Neural Networks Learn. Syat, 30, 12, 3572-3583 (2018)
[13] Tong, S. C.; Li, Y. M., Fuzzy adaptive robust backstepping stabilization for SISO nonlinear systems with unknown virtual control direction, Inf. Sci., 180, 23, 4619-4640 (2010) · Zbl 1205.93136
[14] Li, Y. M.; Yang, T. T.; Tong, S. C., Adaptive neural networks finite-time optimal control for a class of nonlinear systems, IEEE Trans. Neural Networks Learn. Syst. (2019)
[15] Liu, Y. J.; Gong, M. Z.; Tong, S. C.; Philip Chen, C. L.; Li, D. J., Adaptive fuzzy output feedback control for a class of nonlinear systems with full state sonstraints, IEEE Trans. Fuzzy Syst., 26, 5, 2607-2617 (2018)
[16] Shojaei, F.; Arefi, M. M.; Khayatian, A., Observer-based fuzzy adaptive dynamic surface control of uncertain nonstrict feedback systems with unknown control direction and unknown dead-zone, IEEE Trans. Syst. Man Cybern. Syst., 49, 11, 2340-2351 (2019)
[17] Niu, B.; Li, H.; Zhang, Z. Q., Adaptive neural-network-based dynamic surface control for stochastic interconnected nonlinear nonstrict-feedback systems with dead zone, IEEE Trans. Syst. Man Cybern. Syst., 49, 7, 1386-1398 (2019)
[18] Long, L. J.; Zhao, J., Adaptive fuzzy output-feedback dynamic surface control of MIMO switched nonlinear systems with unknown gain signs, Fuzzy Sets Syst., 302, 27-51 (2016) · Zbl 1378.93066
[19] Li, Y. M.; Tong, S. C., Adaptive fuzzy backstepping dynamic surface control of uncertain nonlinear systems based on filter observer, Int. J. Fuzzy Syst., 14, 2, 320-329 (2012)
[20] Zhang, H. G.; Cui, Y.; Wang, Y. C., Hybrid fuzzy adaptive fault-tolerant control for a class of uncertain nonlinear systems with unmeasured states, IEEE Trans. Fuzzy Syst., 25, 5, 1041-1050 (2017)
[21] Li, Y. X., Finite time command filtered adaptive fault tolerant control for a class of uncertain nonlinear systems, Automatica, 106, 117-123 (2019) · Zbl 1429.93181
[22] Cui, Y.; Zhang, H. G.; Wang, Y. C., A fuzzy adaptive tracking control for MIMO switched uncertain nonlinear systems in strict-feedback form, IEEE Trans. Fuzzy Syst., 27, 12, 2443-2452 (2019)
[23] Wen, G. X.; Philip Chen, C. L.; Li, B., Optimized formation control using simplified reinforcement learning for a class of multi-agent systems with unknown dynamics, IEEE Trans. Industr. Electron., 67, 9, 7879-7888 (2020)
[24] D.Y. Li, S.S. Ge, W. He, Multilayer formation control of multi-agent systems, Automatica. doi:10.1016/j.automatica.2019.108558. · Zbl 1429.93024
[25] Wen, G. X.; Philip Chen, C. L.; Liu, Y. J.; Liu, Z., Neural network-based adaptive leader-following consensus control for a class of nonlinear multiagent state-delay systems, IEEE Trans. Cybern., 47, 8, 2151-2160 (2017)
[26] Philip Chen, C. L.; Wen, G. X.; Liu, Y. J.; Liu, Z., Observer-based adaptive backstepping consensus tracking control for high-order nonlinear semi-strict-feedback multiagent systems, IEEE Trans. Cybern., 46, 7, 1591-1601 (2016)
[27] Ren, C. E.; Chen, C. L.P.; Du, T., Fuzzy adaptive leader-following consensus control for nonlinear multi-agent systems with unknown control directions, Int. J. Fuzzy Syst., 21, 7, 2066-2076 (2019)
[28] Mei, J.; Ren, W.; Chen, J., Distributed consensus of second-order multi-agent systems with heterogeneous unknown inertias and control gains under a directed graph, IEEE Trans. Autom. Control, 61, 8, 2019-2034 (2016) · Zbl 1359.93418
[29] Zou, W. C.; Ahn, K.; Xiang, Z. R., Event-triggered consensus tracking control of stochastic nonlinear multiagent systems, IEEE Syst. J., 13, 4, 4051-4059 (2019)
[30] Wang, W.; Liang, H. J.; Zhang, Y. H.; Li, T. S., Adaptive cooperative control for a class of nonlinear multi-agent systems with dead zone and input delay, Nonlinear Dyn., 96, 4, 2707-2719 (2019) · Zbl 1468.93102
[31] Zhao, L.; Yu, J. P.; Lin, C.; Ma, Y. M., Adaptive neural consensus tracking for nonlinear multiagent systems using finite-time command filtered backstepping, IEEE Trans. Syst., Man, Cybern.: Syst., 48, 11, 2003-2012 (2018)
[32] Zou, W. C.; Shi, P.; Xiang, Z. R.; Shi, Y., Consensus tracking control of switched stochastic nonlinear multiagent systems via event-triggered strategy, IEEE Trans. Neural Networks Learn. Syst., 31, 3, 1036-1045 (2020)
[33] H.J. Liang, X.Y. Guo, Y.M. Pan, T.W. Huang, Event-triggered fuzzy bipartite tracking control for network systems based on distributed reduced-order observers, IEEE Trans. Fuzzy Syst. doi:10.1109/TFUZZ.2020.2982618.
[34] Zou, W. C.; Shi, P.; Xiang, Z. R.; Shi, Y., Finite-time consensus of second-order switched nonlinear multi-agent systems, IEEE Trans. Neural Networks Learn. Syst., 31, 5, 1757-1762 (2020)
[35] You, X.; Hua, C. C.; Yu, H. N.; Guan, X. P., Leader-following consensus for high-order stochastic multi-agent systems via dynamic output feedback control, Automatica, 107, 418-424 (2019) · Zbl 1429.93347
[36] Xiao, F.; Chen, T. W.; Gao, H. J., Synchronous hybrid event- and time-driven consensus in multiagent networks with time delays, IEEE Trans. Cybern., 5, 46, 1165-1174 (2016)
[37] Zhuo, S.; Song, Y. D.; Lewis, F. L.; Davoudi, A., Output containment control of linear heterogeneous multi-agent systems using internal model principle, IEEE Trans. Cybern., 47, 8, 2099-2109 (2017)
[38] Y. M, Li, F.Y. Qu, S.C. Tong, Observer-based fuzzy adaptive finite-time containment control of nonlinear multiagent systems with input delay, IEEE Trans. Fuzzy Syst. doi: 10.1109/TCYB.2020.2970454.
[39] H.J. Liang, L.C. Zhang, Y.H. Sun, T.W. Huang, Containment control of semi-markovian multi-agent systems with switching topologies, IEEE Trans. Syst., Man Cybern.: Syst. doi: 10.1109/TSMC.2019.2946248.
[40] Cui, G. Z.; Xu, S. Y.; Chen, X. K.; Lewis, F. L.; Zhang, B. Y., Distributed containment control for nonlinear multiagent systems in pure-feedback form, Int. J. Robust Nonlinear Control, 28, 7, 2742-2758 (2018) · Zbl 1391.93009
[41] Wu, Y. F.; Yue, D., Prescribed performance global stable adaptive neural dynamic surface consensus tracking control of stochastic multi-agent systems with hysteresis inputs and nonlinear dynamics, Int. J. Syst. Sci., 49, 16, 3431-3447 (2018) · Zbl 1482.93573
[42] Wang, W.; Wen, C. Y.; Huang, J. S., Distributed adaptive asymptotically consensus tracking control of nonlinear multi-agent systems with unknown parameters and uncertain disturbances, Automatica, 77, 133-142 (2017) · Zbl 1355.93022
[43] Jia, S. Y.; Shan, J. J., Finite-time trajectory tracking control of space manipulator under actuator saturation, IEEE Trans. Industr. Electron., 67, 3, 2086-2096 (2020)
[44] Zhao, Y. D.; Zhang, S. K.; Li, J., Adaptive finite-time backstepping control for a two-wheeled mobile manipulator, J. Mech. Sci. Technol., 32, 12, 5897-5906 (Dec. 2018)
[45] Liu, Y.; Liu, X. P.; Jing, Y. W.; Chen, X. Y.; Qiu, J. L., Direct adaptive preassigned finite-time control with time-delay and quantized input using neural network, IEEE Trans. Neural Networks Learn. Syst., 31, 4, 1222-1231 (2020)
[46] Liu, C. G.; Wang, H. Q.; Liu, X. P.; Zhou, Y. C., Adaptive finite-time fuzzy funnel control for nonaffine nonlinear systems, IEEE Trans. Syst. Man Cybern. Syst. (2019)
[47] Liu, Y.; Liu, X. P.; Jing, Y. W.; Wang, H. Q.; Li, X. H., Annular domain finite-time connective control for largescale systems with expanding construction, IEEE Trans. Syst. Man Cybern. Syst. (2019)
[48] Zhu, Z.; Xia, Y.; Fu, M., Attitude stabilization of rigid spacecraft with finite-time convergence, Int. J. Robust Nonlinear Control, 21, 6, 686-702 (2011) · Zbl 1214.93100
[49] Wang, F.; Chen, B.; Liu, X. P.; Lin, C., Finite-time adaptive fuzzy tracking control design for nonlinear systems, IEEE Trans. Fuzzy Syst., 26, 3, 1207-1216 (2018)
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.