Abstract
In this paper, the problem of consensus tracking control for a class of distributed nonlinear multiagent systems is studied. Considering the system with nonstrict-feedback structure and sensor faults, an adaptive neural network control scheme is proposed, which combines backstepping technique with radial basis function neural network. In the process of control design, neural network approximation technique and its structural characteristics are used to overcome the control design obstacles caused by unknown nonlinear function and nonstrict-feedback structure. A controller is constructed for the system considering the sensor faults, which can not only realize the consensus tracking control of the system, but also ensure that all signals of the closed-loop system are bounded. Finally, an example is given to show the effectiveness of the proposed scheme.
Supported by National Natural Science Foundation of China under Grant Nos. 61973148.
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References
Wang F (2017) Distributed adaptive neural control for stochastic nonlinear multiagent systems. IEEE Trans. Cybern 47(7):1795–1803
Liang HJ (2019) Containment control of semi-Markovian multiagent systems with switching topologies. IEEE Trans Syst Man Cybern Syst https://doi.org/10.1109/TSMC.2019.2946248
Zhang HW (2012) Lyapunov, adaptive, and optimal design techniques for cooperative systems on directed communication graphs. IEEE Trans Ind Electron 59(7):3026–3041
Shang Y (2020) Consensus tracking control for distributed nonlinear multiagent systems via adaptive neural backstepping approach. IEEE Trans Syst Man Cybern Syst 50(7):150–157
Yoo SJ (2013) Distributed consensus tracking for multiple uncertain nonlinear strict-feedback systems under a directed graph. IEEE Trans Neural Netw Learn Syst 24(3):666–672
Liu M (2020) Robust bipartite consensus and tracking control of high-order multiagent systems with matching uncertainties and antagonistic interactions. IEEE Trans Syst Man Cybern Syst 50(7):2541–2550
Zhou Q (2019) Event-triggered fuzzy adaptive containment control for nonlinear multi-Agent systems with unknown bouc-wen hysteresis input. IEEE Trans Fuzzy Syst https://doi.org/10.1109/TFUZZ.2019.2961642
Qiu JH (2020) On the bipartite consensus for generic linear multiagent systems with input saturation. IEEE Trans Cybern 47(8):1948–1958
Li HY (2017) Adaptive fuzzy control of stochastic nonstrict-feedback nonlinear systems with input saturation. IEEE Trans Syst Man Cybern 47(8):2185–2197
Li YM (2011) Adaptive fuzzy backstepping output feedback control of nonlinear uncertain systems with unknown virtual control coefficients using MT-filters. Neurocomputing 74(10):1557–1563
Wang HQ (2015) Approximation-based adaptive fuzzy tracking control for a class of nonstrict-feedback stochastic nonlinear time-delay systems. IEEE Trans Fuzzy Syst 23(5):1746–17606
Zhou Q (2018) Prescribed performance observer-based adaptive fuzzy control for nonstrict-feedback stochastic nonlinear systems. IEEE Trans Syst Man Cybern Syst 48(10):1747–1758
Cao L (2019) Event-triggered control for multiagent systems with sensor faults and input saturation. IEEE Trans Syst Man Cybern Syst https://doi.org/10.1109/TSMC.2019.2938216
Li WQ (2020) Adaptive-gain observer-based stabilization of stochastic strict-feedback systems with sensor uncertainty. Automatica https://doi.org/10.1016/j.automatica.2020.109112
Xia JW (2019) Finite-time adaptive fuzzy control for nonlinear systems with full state constraints. IEEE Trans Syst Man Cybern Syst 46(7):1541–1548
Sun W (2020) A novel adaptive fuzzy control for output constrained stochastic non-strict feedback nonlinear systems. IEEE Trans Fuzzy Syst https://doi.org/10.1109/TFUZZ.2020.2969909
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Lian, Y., Wang, X., Yang, W., Wang, L., Xia, J., Sun, W. (2022). Consensus Control for Nonlinear Multiagent Systems with Sensor Faults. In: Jing, X., Ding, H., Wang, J. (eds) Advances in Applied Nonlinear Dynamics, Vibration and Control -2021. ICANDVC 2021. Lecture Notes in Electrical Engineering, vol 799. Springer, Singapore. https://doi.org/10.1007/978-981-16-5912-6_51
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DOI: https://doi.org/10.1007/978-981-16-5912-6_51
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