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Advances in Manufacturing

12-07-2023

Leader-follower consensus of nonlinear agricultural multiagents using distributed adaptive protocols

Authors: Yu-Chen Qian, Zhong-Hua Miao, Jin Zhou, Xiao-Jin Zhu

Published in: Advances in Manufacturing

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Abstract

Agricultural multi-agent systems are expected to be fundamental to future intelligent agriculture and digital farming. This study deals with agricultural multirobots from the perspective of the control algorithm, and adaptive leader-following consensus protocol design problems are resolved for nonlinear multiagent systems. A fully distributed edge-based strategy adaptive law is discussed herein; thus, the multiagent consensus can be implemented without knowing global information. Unlike methodologies in existing literature on nonlinear consensus, the proposed methodology is considerably less conservative because of the incremental quadratic constraint containing a wider variety of nonlinearities. This means that, utilizing an incremental multiplier matrix with appropriate values, the control scheme can be applied to a broader class of nonlinear multi-agent systems, which is applicable to more agricultural fields. Finally, a numerical example consisting of six followers and one leader is provided to demonstrate the validity and effectiveness of the proposed protocol under a directed network.

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Costa GB, Damiani JS, Marchesan G et al (2022) A multi-agent approach to distribution system fault section estimation in smart grid environment. Electr Power Syst Res 204:107658. https://doi.org/10.1016/j.epsr.2021.107658CrossRef

Miao Z, Yu J, Ji J et al (2019) Multi-objective region reaching control for a swarm of robots. Automatica 103:81–87MathSciNetCrossRefMATH

Xia W, Cao M, Johansson KH (2016) Structural balance and opinion separation in trust–mistrust social networks. IEEE Trans Control Netw Syst 3(1):46–56MathSciNetCrossRefMATH

Ju C, Kim J, Seol J et al (2022) A review on multirobot systems in agriculture. Comput Electron Agric 202:107336. https://doi.org/10.1016/j.compag.2022.107336CrossRef

Albiero D, Garcia AP, Umezu CK et al (2022) Swarm robots in mechanized agricultural operations: a review about challenges for research. Comput Electron Agric 193:106608. https://doi.org/10.1016/j.compag.2021.106608CrossRef

Su H, Zhang J, Chen X (2019) A stochastic sampling mechanism for time-varying formation of multiagent systems with multiple leaders and communication delays. IEEE Trans Neural Netw Learn Syst 30(12):3699–3707MathSciNetCrossRef

Su H, Wu H, Chen X et al (2018) Positive edge consensus of complex networks. IEEE Trans Syst Man Cybern 48(12):2242–2250CrossRef

Qian Y, Zhang W, Ji M et al (2020) Observer-based positive edge consensus for directed nodal networks. IET Contr Theory Appl 14(2):352–357MathSciNetCrossRef

Wu H, Zhu Z (2022) Improved results on distributed observer-based positive edge consensus. J Frankl Inst-Eng Appl Math. https://doi.org/10.1016/j.jfranklin.2022.05.016CrossRef

10.

Zhao Y, Zhu F, Xu D (2022) Event-triggered bipartite time-varying formation control for multiagent systems with unknown inputs. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2022.3208228CrossRef

11.

Zhang W, Su H, Zhu F et al (2013) Observer-based H∞ synchronization and unknown input recovery for a class of digital nonlinear systems. Circ Syst Signal Process 32(6):2867–2881MathSciNetCrossRef

12.

Wang Z, Xun Y, Wang Y et al (2022) Review of smart robots for fruit and vegetable picking in agriculture. Int J Agric Biol Eng 15(1):33–54MathSciNet

13.

Zhang C, Noguchi N (2017) Development of a multi-robot tractor system for agriculture field work. Comput Electron Agric 142:79–90CrossRef

14.

Li Z, Duan Z, Chen G et al (2010) Consensus of multiagent systems and synchronization of complex networks: a unified viewpoint. IEEE Trans Circuits Syst I-Regul Pap 57(1):213–224MathSciNetCrossRefMATH

15.

Li Z, Ren W, Liu X et al (2013) Consensus of multi-agent systems with general linear and Lipschitz nonlinear dynamics using distributed adaptive protocols. IEEE Trans Autom Control 58(7):1786–1791MathSciNetCrossRefMATH

16.

Yan C, Zhang W, Su H et al (2022) Adaptive bipartite time-varying output formation control for multiagent systems on signed directed graphs. IEEE Trans Cybern 52(9):8987–9000CrossRef

17.

Noguchi N, Will J, Reid J et al (2004) Development of a master–slave robot system for farm operations. Comput Electron Agric 44:1–19CrossRef

18.

Johnson DA, Naffin DJ, Puhalla JS et al (2009) Development and implementation of a team of robotic tractors for autonomous peat moss harvesting. J Field Robot 26(6/7):549–571CrossRef

19.

Zhang W, Su H, Zhu F et al (2012) A note on observers for discrete-time Lipschitz nonlinear systems. IEEE Trans Circuits Syst II-Express Briefs 59(2):123–127CrossRef

20.

Zou W, Shi P, Xiang Z et al (2020) Finite-time consensus of second-order switched nonlinear multi-agent systems. IEEE Trans Syst Man Cybern 31(5):1757–1762MathSciNet

21.

Zou W, Guo J, Ahn CK et al (2022) Sampled-data consensus protocols for a class of second-order switched nonlinear multiagent systems. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2022.3163157CrossRef

22.

Zou W, Zhou C, Guo J et al (2021) Global adaptive leader-following consensus for second-order nonlinear multiagent systems with switching topologies. IEEE Trans Circuits Syst II-Express Briefs 68(2):702–706

23.

Abbaszadeh M, Marquez HJ (2010) Nonlinear observer design for one-sided Lipschitz systems. In: Proceedings of the 2010 American control conference, June 30–July 2, 2010, Baltimore, MD, USA, pp 5284‒5289

24.

Zhang W, Su H, Liang Y et al (2012) Non-linear observer design for one-sided Lipschitz systems: an linear matrix inequality approach. IET Control Theory Appl 6(9):1297–1303MathSciNetCrossRef

25.

Cao Y, Zhang L, Li C et al (2017) Observer-based consensus tracking of nonlinear agents in hybrid varying directed topology. IEEE Trans Cybern 47(8):2212–2222CrossRef

26.

Açıkmeşe B, Corless M (2011) Observers for systems with nonlinearities satisfying incremental quadratic constraints. Automatica 47:1339–1348MathSciNetCrossRefMATH

27.

Zhao Y, Zhang W, Su H et al (2020) Observer-based synchronization of chaotic systems satisfying incremental quadratic constraints and its application in secure communication. IEEE Trans Syst Man Cybern 50(12):5221–5232CrossRef

28.

Wang X, Wang X, Su H et al (2022) Reduced-order interval observer based consensus for MASs with time-varying interval uncertainties. Automatica 135:109989. https://doi.org/10.1016/j.automatica.2021.109989MathSciNetCrossRefMATH

29.

Xu X, Açıkmeşe B, Corless MJ (2021) Observer-based controllers for incrementally quadratic nonlinear systems with disturbances. IEEE Trans Autom Control 66(3):1129–1143MathSciNetCrossRefMATH

30.

Li X, Liu F, Buss M et al (2020) Fully distributed consensus control for linear multiagent systems: a reduced-order adaptive feedback approach. IEEE Trans Control Netw Syst 7(2):967–976MathSciNetCrossRefMATH

31.

Chu H, Liu X, Zhang W et al (2016) Observer-based consensus tracking of multi-agent systems with one-sided Lipschitz nonlinearity. J Frankl Inst-Eng Appl Math 353:1594–1614MathSciNetCrossRefMATH

32.

Yan C, Zhang W, Li X et al (2020) Observer-based time-varying formation tracking for one-sided Lipschitz nonlinear systems via adaptive protocol. Int J Control Autom Syst 18:2753–2764CrossRef

33.

Li S, Ahn CK, Guo J et al (2021) Neural network-based sampled-data control for switched uncertain nonlinear systems. IEEE Trans Syst Man Cybern 51(9):5437–5445CrossRef

34.

Yu Y, Guo J, Ahn CK et al (2022) Neural adaptive distributed formation control of nonlinear multi-UAVs with unmodeled dynamics. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2022.3157079CrossRef

35.

Zhang Y, Guo J, Xiang Z (2022) Finite-time adaptive neural control for a class of nonlinear systems with asymmetric time-varying full-state constraints. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/TNNLS.2022.3164948CrossRef

36.

Yu J, Dong X, Li Q et al (2018) Practical time-varying formation tracking for second-order nonlinear multiagent systems with multiple leaders using adaptive neural networks. IEEE Trans Neural Netw Learn Syst 29(12):6015–6025MathSciNetCrossRef

Title: Leader-follower consensus of nonlinear agricultural multiagents using distributed adaptive protocols
Authors: Yu-Chen Qian
Zhong-Hua Miao
Jin Zhou
Xiao-Jin Zhu
Publication date: 12-07-2023
Publisher: Shanghai University
Published in: Advances in Manufacturing
Print ISSN: 2095-3127
Electronic ISSN: 2195-3597
DOI: https://doi.org/10.1007/s40436-023-00449-x

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