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Soft Computing

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03.02.2016 | Methodologies and Application

Interval fuzzy sliding-mode formation controller design

verfasst von: Chia-Wen Chang, Cheng-Yuan Yang, Chin-Wang Tao

Erschienen in: Soft Computing | Ausgabe 14/2017

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Abstract

This paper focuses on the design of a formation controller for multi-robot dynamic systems using interval fuzzy sliding-mode algorithm. The objective of formation control is to have all robots simultaneously achieve the tracking task with the desired pattern. An interval fuzzy sliding-mode formation controller is proposed to deal with the formation control of multi-robot systems in which the system uncertainties and measured noise are considered. To reduce the computational complexity of a type-reducer, the end points of a type-reduced centroid are approximated by the outputs of two standard fuzzy sliding mechanisms in the proposed interval fuzzy sliding controller. Simulation results are indicated to show the effectiveness of the proposed interval fuzzy sliding-mode consensus controller.

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Baten MA, Kamil AA (2012) Fuzzy optimal control with application to discounted profit advertising problem. J Intell Fuzzy Syst 23(5):187–192MathSciNetMATH

Chang YH, Chang CW, Chen CL, Tao CW (2012a) Fuzzy sliding-mode formation control for multirobot systems: Design and implementation. IEEE Trans Syst Man Cybern Part B Cybern 42(2):444–457

Chang YH, Chang CW, Tao CW, Lin HW, Taur JS (2012b) Fuzzy sliding-mode control for ball and beam system with fuzzy ant colony optimization. Expert Syst Applicat 39(3):3624–3633CrossRef

Cheng L, Hou Z, Tan M (2013) A mean square consensus protocol for linear multi-agent systems with communication noises and fixed topologies. Autom Control IEEE Trans 59:261–267

Deperlioglu O (2013) Power electronics converter control based on rule based algorithm. J Intell Fuzzy Syst 24(4):703–711

Dias MB, Zlot R, Kalra N, Stentz A (2006) Market-based multirobot coordination: a survey and analysis. Proc IEEE 94(7):1257–1270CrossRef

Feng X, Butler-Purry KL, Zourntos T (2012) Multi-agent system-based real-time load management for all-electric ship power systems in dc zone level. Power Syst IEEE Trans 27(4):1719–1728CrossRef

Hu J, Xu Z (2013) Brief paper—distributed cooperative control for deployment and task allocation of unmanned aerial vehicle networks. Control Theory Appl IET 7(11):1574–1582MathSciNetCrossRef

Hwang KS, Tan SW, Hsiao MC, Wu CS (2005) Cooperative multiagent congestion control for high-speed networks. Syst Man Cybern Part B Cybern IEEE Trans 35(2):255–268CrossRef

Jenie Y, Kampen EJ, Remes B (2013) Cooperative autonomous collision avoidance system for unmanned aerial vehicle, Chap. 24. Springer, Berlin, Heidelberg, pp 387–405

Ko AHR, Sabourin R, Gagnon F (2013) Performance of distributed multi-agent multi-state reinforcement spectrum management using different exploration schemes. Expert Syst Appl 40(10):4115–4126CrossRef

Lee D (2010) Passive decomposition and control of nonholonomic mechanical systems. Robot IEEE Trans 26(6):978–992CrossRef

Li Z, Ren W, Liu X, Xie L (2013) Distributed consensus of linear multi-agent systems with adaptive dynamic protocols. Automatica 49(7):1986–1995MathSciNetCrossRefMATH

Ni W, Cheng D (2010) Leader-following consensus of multi-agent systems under fixed and switching topologies. Syst Control Lett 59(34):209–217MathSciNetCrossRefMATH

Olfati-Saber R, Fax JA, Murray RM (2007) Consensus and cooperation in networked multi-agent systems. Proc IEEE 95(1):215–233CrossRef

Oliveira JL, Davies MEP, Gouyon F, Reis LP (2012) Beat tracking for multiple applications: A multi-agent system architecture with state recovery. Audio Speech Lang Process IEEE Trans 20(10):2696–2706CrossRef

Ren W, Beard R (2007) Distributed consensus in multi-vehicle cooperative control: theory and applications. Springer, New York

Ren W, Sorensen N (2008) Distributed coordination architecture for multi-robot formation control. Robot Auton Syst 56(4):324–333CrossRefMATH

Ren W, Beard RW, Atkins EM (2007) Information consensus in multivehicle cooperative control. Control Syst IEEE 27(2):71–82CrossRef

Sethi P, Chauhan N, Juneja D (2013) A multi-agent hybrid protocol for data fusion and data aggregation in non-deterministic wireless sensor networks. In: Information systems and computer networks (ISCON), International Conference on, pp 211–214

Tao CW, Chan ML, Lee TT (2003) Adaptive fuzzy sliding mode controller for linear systems with mismatched time-varying uncertainties. IEEE Trans Syst Man Cybern Part B Cybern 33(2):283–294

Wu H, Mendel JM (2002) Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems. Fuzzy Syst IEEE Trans 10(5):622–639CrossRef

Zadeh LA (1975) The concept of a linguistic variable and its application to approximate reasoningi. Inf Sci 8(3):199–249CrossRefMATH

Titel: Interval fuzzy sliding-mode formation controller design
verfasst von: Chia-Wen Chang
Cheng-Yuan Yang
Chin-Wang Tao
Publikationsdatum: 03.02.2016
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 14/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-016-2055-8

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