Abstract
The aim of this chapter is to provide a systematic understanding of the distributed average tracking algorithm design under an extended proportional–integral (PI) framework (The results of this chapter are mainly based on [7]. Section 4.2 is newly added. Additionally, we have added the proof for Theorem 4.2, which was not included in [7] due to space limitation, and we have added a simulation section. See full copyright acknowledgement for non-original material at the end of the chapter). Three different kinds of references are considered: references with steady states, references with bounded derivatives, and references with a common derivative. Compared with the nonsmooth algorithm investigated in the last chapter, the algorithms proposed in this chapter are all smooth; thus overcoming certain undesirable features of nonsmooth algorithms, such as the chattering effect.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
The results of this chapter are mainly based on [7]. Section 4.2 is newly added. Additionally, we have added the proof for Theorem 4.2, which was not included in [7] due to space limitation, and we have added a simulation section. See full copyright acknowledgement for non-original material at the end of the chapter.
References
A.P. Aguiar, J.P. Hespanha, Trajectory-tracking and path-following of underactuated autonomous vehicles with parametric modeling uncertainty. IEEE Trans. Autom. Control 52(8), 1362–1379 (2007)
H. Bai, M. Arcak, J.T. Wen, Adaptive motion coordination: using relative velocity feedback to track a reference velocity. Automatica 45(4), 1020–1025 (2009)
H. Bai, R.A. Freeman, K.M. Lynch, Robust dynamic average consensus of time-varying inputs, in Proceedings of the IEEE Conference on Decision and Control (2010), pp. 3104–3109
H. Bai, R.A. Freeman, K.M. Lynch, Distributed Kalman filtering using the internal model average consensus estimator, in Proceedings of the American Control Conference (2011), pp. 1500–1505
C. Cheah, S. Hou, J. Slotine, Region following formation control for multi-robot systems, in Proceedings of the IEEE International Conference on Robotics and Automation (2008), pp. 3796–3801
F. Chen, Y. Cao, W. Ren, Distributed average tracking of multiple time-varying reference signals with bounded derivatives. IEEE Trans. Autom. Control 56(12), 3169–3174 (2012)
F. Chen, G. Feng, L. Liu, W. Ren, Distributed average tracking of networked Euler-Lagrange systems. IEEE Trans. Autom. Control 60(2), 547–552 (2015)
F. Chen, W. Ren, W. Lan, G. Chen, Tracking the average of time-varying nonsmooth signals for double-integrator agents with a fixed topology, in Proceedings of American Control Conference (2013)
F. Chen, L. Xiang, W. Lan, G. Chen, Coordinated tracking in mean square for a multi-agent system with noisy channels and switching directed network topologies. IEEE Trans. Circuits Syst. II: Express Briefs 59(11), 835–839 (2012)
R.A. Freeman, P. Yang, K.M. Lynch, Stability and convergence properties of dynamic average consensus estimators, in Proceedings of the IEEE Conference on Decision and Control (2006), pp. 338–343
J. Li, W. Ren, S. Xu, Distributed containment control with multiple dynamic leaders for double-integrator dynamics using only position measurements. IEEE Trans. Autom. Control 57(6), 1553–1559 (2012)
P. Lin, Y. Jia, Average consensus in networks of multi-agents with both switching topology and coupling time-delay. Phys. A: Stat. Mech. Its Appl. 387(1), 303–313 (2008)
S. Nosrati, M. Shafiee, M. Menhaj, Dynamic average consensus via nonlinear protocols. Automatica 48(9), 2262–2270 (2012)
R. Olfati-Saber, R.M. Murray, Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans. Autom. Control 49(9), 1520–1533 (2004)
E. Panteley, A. Loria, Growth rate conditions for uniform asymptotic stability of cascaded time-varying systems. Automatica 37(3), 453–460 (2001)
W. Ren, R.W. Beard, Consensus seeking in multiagent systems under dynamically changing interaction topologies. IEEE Trans. Autom. Control 50(5), 655–661 (2005)
W. Ren, R.W. Beard, E.M. Atkins, Information consensus in multivehicle cooperative control: collective group behavior through local interaction. IEEE Control. Syst. Mag. 27(2), 71–82 (2007)
J.-J.E. Slotine, W. Li, Applied Nonlinear Control (Prentice Hall, New Jersey, 1991)
D.P. Spanos, R.M. Murray, Distributed sensor fusion using dynamic consensus, in Proceedings of the IFAC World Congress (2005)
D.P. Spanos, R. Olfati-Saber, R.M. Murray, Dynamic consensus on mobile networks, in Proceedings of The 16th IFAC World Congress (2005)
D. Sun, X. Shao, G. Feng, A model-free cross-coupled control for position synchronization of multi-axis motions: theory and experiments. IEEE Trans. Control. Syst. Technol. 15(2), 306–314 (2007)
Y.G. Sun, L. Wang, G. Xie, Average consensus in networks of dynamic agents with switching topologies and multiple time-varying delays. Syst. Control. Lett. 57(2), 175–183 (2008)
P. Yang, R.A. Freeman, K.M. Lynch, Multi-agent coordination by decentralized estimation and control. IEEE Trans. Autom. Control 53(11), 2480–2496 (2008)
Acknowledgements
©2015 IEEE. Reprinted, with permission, from Fei Chen, Gang Feng, Lu Liu, and Wei Ren. “Distributed average tracking of networked Euler-Lagrange systems.” IEEE Transactions on Automatic Control, vol. 60, no. 2, pp. 547–552, 2015.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Chen, F., Ren, W. (2020). Distributed Average Tracking via an Extended PI Scheme. In: Distributed Average Tracking in Multi-agent Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-39536-0_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-39536-0_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-39535-3
Online ISBN: 978-3-030-39536-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)