Abstract
This paper studies the adaptive fuzzy control problem for multi-agent systems (MASs) with dead zone and input delay. Second-order tracking differentiator is introduced to avoid the repeated differentiations of the virtual control. The problem of dead zone is solved by using dead-zone slope and boundary value theory. Based on the Pade approximation method, the influence of input delay is eliminated of the MASs. The designed controller can guarantee all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and tracking errors converge to a neighbourhood around the origin. Finally, the simulation results show the effectiveness of the proposed method.
Similar content being viewed by others
References
Zheng, Y., Ma, J., Wang, L.: Consensus of hybrid multi-agent systems. IEEE Trans. Neural Netw. Learn. Syst. 29(4), 1359–1365 (2018)
Liu, L., Liu, Y., Tong, S.: Fuzzy based multi-error constraint control for switched nonlinear systems and its applications. IEEE Trans. Fuzzy Syst. (2018). https://doi.org/10.1109/TFUZZ.2018.2882173
Li, D., Chen, C.L.P., Liu, Y., Tong, S.: Neural network controller design for a class of nonlinear delayed systems with time-varying state constraints. IEEE Trans. Neural Netw. Learn. Syst. (2018). https://doi.org/10.1109/TNNLS.2018.2886023
Liang, H., Zhang, Z., Choon, K.A.: Event-triggered fault detection and isolation of discrete-time systems based on geometric technique. IEEE Trans. Circuits Syst. II: Express Briefs. https://doi.org/10.1109/TCSI-I.2019.2907706
Ma, T., Zhang, Z., Cui, B.: Adaptive consensus of multi-agent systems via odd impulsive control. Neurocomputing 321, 139–145 (2018)
Ma, T., Yu, T., Cui, B.: Adaptive synchronization of multi-agent systems via variable impulsive control. J. Frankl. Inst. 355(15), 7490–7508 (2018)
Zou, W., Xiang, Z., Ahn, C.K.: Mean square leader-following consensus of second-order nonlinear multi-agent systems with noises and unmodeled dynamics. IEEE Trans. Syst. Man Cybern. Syst. (2018). https://doi.org/10.1109/TSMC.2018.2862140
Cao, L., Li, H., Wang, N., Zhou, Q.: Observer-based event-triggered adaptive decentralized fuzzy control for nonlinear large-scale systems. IEEE Trans. Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2018.2873971
Zou, W., Xiang, Z.: Event-triggered leader-following consensus of non-linear multi-agent systems with switched dynamics. IET Control Theory Appl. (2018). https://doi.org/10.1049/iet-cta.2018.5126
Sun, N., Yang, T., Fang, Y., Wu, Y., Chen, H.: Transportation control of double-pendulum cranes with a nonlinear quasi-PID scheme: design and experiments. IEEE Trans. Syst Man Cybern. Syst. (2018). https://doi.org/10.1109/TSMC.2018.2871627
Sun, N., Yang, T., Chen, H., Fang, Y., Qian, Y.: Adaptive anti-swing and positioning control for 4-DOF rotary cranes subject to uncertain/unknown parameters with hardware experiments. IEEE Trans. Syst. Man Cybern. Syst. (2018). https://doi.org/10.1109/TSMC.2017.2765183
Liang, H., Zhang, L., Karimi, H., Zhou, Q.: Fault estimation for a class of nonlinear semi-Markovian jump systems with partly unknown transition rates and output quantization. Int. J. Robust Nonlinear Control 28(18), 5962–5980 (2018)
Zou, A., Kumar, K.: Neural network-based adaptive output feedback formation control for multi-agent systems. Nonlinear Dyn. 70(2), 1283–1296 (2012)
Qi, H., Iyengar, S., Chakrabarty, K.: Multiresolution data integration using mobile agents in distributed sensor networks. IEEE Trans. Syst. Man Cybern. C (Appl. Rev.) 31(3), 383–391 (2001)
Saska, M., Vonásek, V., Chudoba, J., Thomas, J., Loianno, G., Kumar, V.: Swarm distribution and deployment for cooperative surveillance by micro-aerial vehicles. J. Intell. Robot. Syst. 84(1–4), 469–492 (2016)
Prorok, A., Hsieh, M.A., Kumar, V.: The impact of diversity on optimal control policies for heterogeneous robot swarms. IEEE Trans. Robot. 33(2), 346–358 (2017)
Zhang, Y., Li, H., Sun, J., He, W.: Cooperative adaptive event-triggered control for multi-agent systems with actuator failures. IEEE Trans. Syst. Man Cybern. Syst. (2018). https://doi.org/10.1109/TSMC.2018.2883907
Liang, H., Zhou, Y., Ma, H., Zhou, Q.: Adaptive distributed observer approach for cooperative containment control of nonidentical networks. IEEE Trans. Syst. Man Cybern. Syst. 49(2), 299–307 (2019)
Shahvali, M., Shojaei, K.: Distributed adaptive neural control of nonlinear multi-agent systems with unknown control directions. Nonlinear Dyn. 83(4), 2213–2228 (2016)
Xu, X., Li, Z., Gao, L.: Distributed adaptive tracking control for multi-agent systems with uncertain dynamics. Nonlinear Dyn. 90(4), 2729–2744 (2017)
Zhang, Y., Sun, J., Liang, H., Li, H.: Event-triggered adaptive tracking control for multi-agent systems with unknown disturbances. IEEE Trans. Cybern. (2018). https://doi.org/10.1109/TCYB.2018.2869084
Zhang, Z., Liang, H., Wu, C., Ahn, C.K.: Adaptive event-triggered output feedback fuzzy control for nonlinear networked systems with packet dropouts and random actuator failure. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2891236
Zhou, Q., Zhao, S., Li, H., Lu, R., Wu, C.: Adaptive neural network tracking control for robotic manipulators with dead-zone. IEEE Trans. Neural Netw. Learn. Syst. https://doi.org/10.1109/TNNLS.2018.286937
Ogren, P., Fiorelli, E., Leonard, N.E.: Consensus and cooperation in networked multi-agent systems. Cooperative control of mobile sensor networks: adaptive gradient climbing in a distributed environment. IEEE Trans. Autom. Control 49(8), 1292–1302 (2004)
Zhou, J., Wen, C., Zhang, Y.: Adaptive output control of nonlinear systems with uncertain dead-zone nonlinearity. IEEE Trans. Autom. Control 51(3), 504–511 (2006)
Tao, G., Kokotovic, P.: Adaptive control of plants with unknown dead-zones. IEEE Trans. Autom. Control 39(1), 59–68 (1994)
Shen, Q., Shi, P.: Output consensus control of multiagent systems with unknown nonlinear dead zone. IEEE Trans. Syst. Man Cybern. Syst. 46(10), 1329–1337 (2016)
Chen, B., Zhang, H., Liu, X., Lin, C.: Neural observer and adaptive neural control design for a class of nonlinear systems. IEEE Trans. Neural Netw. Learn. Syst. 29(9), 4261–4271 (2018)
Zhang, Z., He, Y., Wu, M., Wang, Q.: Exponential synchronization of neural networks with time-varying delays via dynamic intermittent output feedback control. IEEE Trans. Syst. Man Cybern. Syst. (2018). https://doi.org/10.1109/TSMC.2017.2753944
Mazenc, F., Bliman, P.: Backstepping design for time-delay nonlinear systems. IEEE Trans. Autom. Control 51(1), 149–154 (2006)
Zhou, J., Wen, C., Wang, W.: Adaptive backstepping control of uncertain systems with unknown input time-delay. Automatica 45(6), 1415–1422 (2009)
Li, Z., Hu, G.: Consensus of linear multi-agent systems with communication and input delays. ACTA Autom. Sin. 39(7), 1133–1140 (2013)
Zhu, W., Chen, B., Yang, J.: Consensus of fractional-order multi-agent systems with input time delay. Fract. Calc. Appl. Anal. 20(1), 52–70 (2017)
Lin, P., Jia, Y.: Consensus of a class of second-order multi-agent systems with time-delay and jointly-connected topologies. IEEE Trans. Autom. Control 55(3), 778–784 (2010)
Liang, H., Zhang, Y., Huang, T., Ma, H.: Prescribed performance cooperative control for multiagent systems with input quantization. IEEE Trans. Cybern. (2019). https://doi.org/10.1109/TCYB.2019.2893645
Ma, H., Li, H., Liang, H., Dong, G.: Adaptive fuzzy event-triggered control for stochastic nonlinear systems with full state constraints and actuator faults. IEEE Trans. Fuzzy Syst. https://doi.org/10.1109/TFUZZ.2019.2896843
Swaroop, D., Hedrick, J., Yip, P., Gerdes, J.: Dynamic surface control for a class of nonlinear systems. IEEE Trans. Autom. Control 45(10), 1893–1899 (2000)
Ma, J., Zheng, Z., Li, P.: Adaptive dynamic surface control of a class of nonlinear systems with unknown direction control gains and input saturation. IEEE Trans. Cybern. 45(4), 728–741 (2015)
Zhang, T., Ge, S.S.: Adaptive dynamic surface control of nonlinear systems with unknown dead zone in pure feedback form. Automatica 44(7), 1895–1903 (2008)
Wu, X., Wu, X., Luo, X.: Adaptive neural network dynamic surface control for a class of nonlinear systems with uncertain time delays. Int. J. Autom. Comput. 13(4), 1–8 (2016)
Li, Y., Yang, G., Tong, S.: Fuzzy adaptive distributed event-triggered consensus control of uncertain nonlinear multiagent systems. IEEE Trans. Syst. Man Cybern. Syst. (2018). https://doi.org/10.1109/TSMC.2018.2812216
Khanesar, M., Kaynak, O., Yin, S., Gao, H.: Adaptive indirect fuzzy sliding mode controller for networked control systems subject to time-varying network-induced time delay. IEEE Trans. Fuzzy Syst. 23(1), 205–214 (2015)
Lu, K., Liu, Z., Lai, G., Zhang, Y., Chen, C.P.: Adaptive fuzzy tracking control of uncertain nonlinear systems subject to actuator dead zone with piecewise time-varying parameters. IEEE Trans. Fuzzy Syst. (2018). https://doi.org/10.1109/TFUZZ.2018.2882170
Zhang, Y., Sun, J., Liang, H., Li, H.: Event-triggered adaptive tracking control for multiagent systems with unknown disturbances. IEEE Trans. Cybern. (2018). https://doi.org/10.1109/TCYB.2018.2869084
Li, Y., Tong, S., Liu, Y., Li, T.: Adaptive fuzzy robust output feedback control of nonlinear systems with unknown dead zones based on a small-gain approach. IEEE Trans. Fuzzy Syst. 22(1), 164–176 (2014)
Chen, K., Wang, J., Zhang, Y., Liu, Z.: Leader-following consensus for a class of nonlinear strick-feedback multiagent systems with state time-delays. IEEE Trans. Syst. Man Cybern. Syst. (2018). https://doi.org/10.1109/TSMC.2018.2813399
Wang, L., Ying, H.: Adaptive fuzzy systems and control: design and stability analysis. J. Intell. Fuzzy Syst. Appl. Eng. Technol. 3(2), 187 (1995)
Chen, B., Liu, X., Lin, C.: Observer and adaptive fuzzy control design for nonlinear strict-feedback systems with unknown virtual control coefficients. IEEE Trans. Fuzzy Syst. 26(3), 1732–1743 (2018)
Wang, W., Wang, D., Peng, Z.: Predictor-based adaptive dynamic surface control for consensus of uncertain nonlinear systems in strict-feedback form. Int. J. Adapt. Control Signal Process. 31(1), 68–82 (2017)
Wang, W., Tong, S.: Adaptive fuzzy bounded control for consensus of multiple strict-feedback nonlinear systems. IEEE Trans. Cybern. 48(2), 522–531 (2018)
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Funding
This work was partially supported by the National Natural Science Foundation of China (61703051), the Science and Technology Innovation Funds of Dalian (under Grant No. 2018J11CY022), Guangdong Natural Science Funds for Distinguished Young Scholar (2017A- 030306014), Department of Education of Guangdong Province (2017KZDXM027), Department of Education of Liaoning Province (LZ2017001), PhD Start-up Fund of Liaoning Province (20170520124), and Innovative Research Team Program of Guangdong Province Science Foundation (2018B030312006).
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Wang, W., Liang, H., Zhang, Y. et al. Adaptive cooperative control for a class of nonlinear multi-agent systems with dead zone and input delay. Nonlinear Dyn 96, 2707–2719 (2019). https://doi.org/10.1007/s11071-019-04954-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11071-019-04954-2