Skip to main content
Log in

Observer-based Time-varying Formation Tracking for One-sided Lipschitz Nonlinear Systems via Adaptive Protocol

  • Published:
International Journal of Control, Automation and Systems Aims and scope Submit manuscript

Abstract

In this paper, we investigate the problem of observer-based time-varying leader-following formation tracking for multi-agent systems with the one-sided Lipschitz and quadratic inner-boundedness nonlinear dynamics. An idea of the observer-based protocol with an edge-based adaptive law is designed for nonlinear systems, which enable agents to achieve a desired formation tracking when it cannot obtain the full state of the nonlinear system. In contrast to the previous nonlinear formation systems, the advantage of the developed method is that it is less conservative and more general for the nonlinear system with large Lipschitz constants. Besides, under the proposed adaptive law, the design of the protocol does not rely on the known communication topology. Finally, the simulation results for one leader and six followers are proposed to show the feasibility and effectiveness of the proposed method in the nonlinear time-varying formation system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. H. Su, J. Zhang, and X. Chen, “A stochastic sampling mechanism for time-varying formation of multiagent systems with multiple leaders and communication delays,” IEEE Trans. on Neural Networks and Learning Systems, vol. 30, no. 12, pp. 3699–3707, December 2019.

    MathSciNet  Google Scholar 

  2. Z. Li, W. Ren, X. Liu, and M. Fu, “Consensus of multiagent systems with general linear and Lipschitz nonlinear dynamics using distributed adaptive protocols,” IEEE Trans. on Automatic Control, vol. 58, no. 7, pp. 1786–1791, July 2013.

    MathSciNet  MATH  Google Scholar 

  3. H. Ren and G. Zong, and H. R. Karimi, “Asynchronous finite-time filtering of networked switched systems and its application: an event-driven method,” IEEE Trans. on Circuits and Systems I: Regular Papers, vol. 66, no. 1, pp. 391–402, January 2019.

    MathSciNet  Google Scholar 

  4. H. Su, H. Wu, X. Chen, and M. Z. Q. Chen, “Positive edge consensus of complex networks,” IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 48, no. 12, pp. 2242–2250, December 2018.

    Google Scholar 

  5. H. Su, H. Wu, and J. Lam, “Positive edge-consensus for nodal networks via output feedback,” IEEE Trans. on Automatic Control, vol. 64, no. 3, pp. 1244–1249, March 2019.

    MathSciNet  MATH  Google Scholar 

  6. X. Wang, H. Su, M. Z. Q. Chen, and X. Wang, “Observer-Based robust coordinated control of multiagent systems with input saturation,” IEEE Trans. on Neural Networks and Learning Systems, vol. 29, no. 5, pp. 1933–1946, May 2018.

    MathSciNet  Google Scholar 

  7. D. Zhang, Z. Xu, H. R. Karimi, Q. Wang, and L. Yu, “Distributed H output-feedback control for consensus of heterogeneous linear multiagent systems with aperiodic sampled-data communications,” IEEE Trans. on Industrial Electronics, vol. 65, no. 5, pp. 4145–4155, May 2018.

    Google Scholar 

  8. Y. Qian, W. Zhang, M. Ji, and C. Yan, “Observer-based positive edge consensus for directed nodal networks,” IET Control Theory Applications, vol. 14, no. 2, pp. 352–357, January 2020.

    Google Scholar 

  9. J. Liu, J. Fang, Z. Li, and G. He, “Formation control with multiple leaders via event-triggering transmission strategy,” International Journal of Control, Automation and Systems, vol. 17, no. 6, pp. 1494–1506, May 2019.

    Google Scholar 

  10. J. Bai, G. Wen, Y. Song, and Y. Yu, “Distributed formation control of fractional-order multi-agent systems with relative damping and communication delay,” International Journal of Control, Automation and Systems, vol. 15, no. 1, pp. 85–94, December 2017.

    Google Scholar 

  11. Y. Wang, Y. Wei, X. Liu, N. Zhou, and C. G. Cassandras, “Optimal persistent monitoring using second-order agents with physical constraints,” IEEE Trans. on Automatic Control, vol. 64, no. 8, pp. 3239–3252, August 2019.

    MathSciNet  MATH  Google Scholar 

  12. Y. Wang, M. Zhao, W. Yang, N. Zhou, and C. G. Cassandras, “Collision-free trajectory design for 2D persistent monitoring using second-order agents,” IEEE Trans. on Control of Network Systems, doi: https://doi.org/10.1109/TCNS.2019.2954970, 2019.

  13. H. R. Karimi, H. Zhang, and S. Ding, “Advanced methods in control and signal processing for complex marine systems,” ISA Transactions, vol. 78, pp. 1–2, July 2018.

    Google Scholar 

  14. X. Wang and H. Su, “Self-triggered leader-following consensus of multi-agent systems with input time delay,” Neurocomputing, vol. 330, pp. 70–77, February 2019.

    Google Scholar 

  15. H. Su, X. Chen, M. Z. Q. Chen, and L. Wang, “Distributed estimation and control for mobile sensor networks with coupling delays,” ISA Transactions, vol. 64, pp. 141–150, September 2016.

    Google Scholar 

  16. S. Aouaouda, M. Chadli, M. Boukhnifer, and H. R. Karimi, “Robust fault tolerant tracking controller design for vehicle dynamics: A descriptor approach,” Mechatronics, vol. 30, pp. 316–326, September 2015.

    Google Scholar 

  17. H. Su, M. Z. Q. Chen, X. Wang, and J. Lam, “Semiglobal observer-based leader-following consensus with input saturation,” IEEE Trans. on Industrial Electronics, vol. 61, no. 6, pp. 2842–2850, June 2014.

    Google Scholar 

  18. Y. Cao and W. Ren, “Finite-time consensus for multi-agent networks with unknown inherent nonlinear dynamics,” Automatica, vol. 50, no. 10, pp. 2648–2656, October 2014.

    MathSciNet  MATH  Google Scholar 

  19. J. Baek, M. Jin, and S. Han, “A new adaptive sliding-mode control scheme for application to robot manipulators,” IEEE Trans. on Industrial Electronics, vol. 63, no. 6, pp. 3628–3637, June 2016.

    Google Scholar 

  20. W. Zhang, H. Su, Y. Liang, and Z. Han, “Non-linear observer design for one-sided Lipschitz systems: An linear matrix inequality approach,” IET Control Theory and Applications, vol. 6, no. 9, pp. 1297–1303, June 2012.

    MathSciNet  Google Scholar 

  21. M. Abbaszadeh, and H. J. Marquez, “Nonlinear observer design for one-sided Lipschitz systems,” Proc. of the 2010 American Control Conf., pp. 5284–5289, 2010.

  22. R. Agha, M. Rehan, C. K. Ahn, G. Mustafa, and S. Ahmad, “Adaptive distributed consensus control of one-sided Lipschitz nonlinear multiagents,” IEEE Trans. on Systems, Man, and Cybernetics: Systems, vol. 49, no. 3, pp. 568–578, March 2019.

    Google Scholar 

  23. R. Wu, W. Zhang, F. Song, Z. Wu, and W. Guo, Observer-based stabilization of one-sided Lipschitz systems with application to flexile link manipulator, Advances in Mechanical Engineering, vol. 7, no. 12, pp. 1–8, December 2015.

    Google Scholar 

  24. Y. Wang, Y. Lei, T. Bian, and Z. Guan, “Distributed control of nonlinear multiagent systems with unknown and non-identical control directions via event-triggered communication,” IEEE Trans. on Cybernetics, vol. 50, no. 5, pp. 1820–1832, May 2020.

    Google Scholar 

  25. J. Liu, J. Fang, Z. Li, and G. He, “Time-varying formation tracking for second-order multi-agent systems subjected to switching topology and input saturation,” International Journal of Control, Automation and Systems, vol. 18, no. 4, pp. 991–1001, April 2020.

    Google Scholar 

  26. P. Wang and B. Ding, “Distributed RHC for tracking and formation of nonholonomic multi-vehicle systems,” IEEE Trans. on Automatic Control, vol. 59, no. 6, pp. 1439–1453, June 2014.

    MathSciNet  MATH  Google Scholar 

  27. B. S. Park and S. J. Yoo, “Adaptive leader-follower formation control of mobile robots with unknown skidding and slipping effects,” International Journal of Control, Automation and Systems, vol. 13, no. 3, pp. 587–594, February 2015.

    Google Scholar 

  28. X. Dong, L. Han, Q. Li, Jian Chen, and Z. Ren, “Time-varying formation tracking for second-order multi-agent systems with one leader,” Chinese Automation Congress, pp. 1046–1051, 2015.

  29. X. Dong and G. Hu, “Time-varying formation tracking for linear multi-agent systems with multiple leaders,” IEEE Trans. on Automatic Control, vol. 62, no. 7, pp. 3658–3664, July 2017.

    MathSciNet  MATH  Google Scholar 

  30. M. Ran, L. Xie, and J. Li, “Time-varying formation tracking for uncertain second-order nonlinear multi-agent systems,” Frontiers of Information Technology & Electronic Engineering, vol. 20, no. 1, pp. 76–87, January 2019.

    Google Scholar 

  31. J. Wang, X. Luo, X. Li, M. Zhu, and X. Guan, “Sliding mode formation control of nonlinear multi-agent systems with local Lipschitz continuous dynamics,” Journal of Systems Science and Complexity, vol. 32, pp. 759–777, June 2019.

    MathSciNet  MATH  Google Scholar 

  32. W. Li, Z. Chen, and Z. Liu, “Leader-following formation control for second-order multiagent systems with time-varying delay and nonlinear dynamics,” Nonlinear Dynamics, vol. 72, no. 4, pp. 803–812, June 2013.

    MathSciNet  MATH  Google Scholar 

  33. J. Yu, X. Dong, Q. Li, and Z. Ren, “Practical time-varying formation tracking for second-order nonlinear multiagent aystems with multiple leaders using adaptive neural networks,” IEEE Trans. on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6015–6025, December 2018.

    MathSciNet  Google Scholar 

  34. Y. Zhang, P. Shi, S. K. Nguang, H. R. Karimi, “Observer-based finite-time fuzzy H control for discrete-time systems with stochastic jumps and time-delays,” Signal Processing, vol. 97, pp. 252–261, April 2014.

    Google Scholar 

  35. X. Li, F. Zhu, and J. Zhang, “State estimation and simultaneous unknown input and measurement noise reconstruction based on adaptive H observer,” International Journal of Control, Automation and Systems, vol. 14, no. 3, pp. 647–654, June 2016.

    Google Scholar 

  36. S. Guo, F. Zhu, and W. Zhang, “Fault detection and reconstruction for discrete nonlinear systems via Takagi-Sugeno fuzzy models,” International Journal of Control, Automation and Systems, vol. 16, no. 6, pp. 2676–2687, October 2018.

    Google Scholar 

  37. W. Zhang, H. Su, F. Zhu, and M. Wang, “Observer-based H synchronization and unknown input recovery for a class of digital nonlinear systems,” Circuits, Systems, and Signal Processing, vol. 32, no. 6, pp. 2867–2881, June 2013.

    MathSciNet  Google Scholar 

  38. C. Wang, Z. Zuo, Q. Gong, and Z. Ding, “Formation control with disturbance rejection for a class of Lipschitz nonlinear systems,” Science China Information Sciences, vol. 60, no. 7, pp. 29–39, June 2017.

    MathSciNet  Google Scholar 

  39. J. Yu, X. Dong, Q. Li, and Z. Ren, “Distributed observer-based time-varying formation tracking for high-order multi-agent systems with nonlinear dynamics,” Proc. of 36th Chinese Control Conf., pp. 8583–8588, 2017.

  40. E. Hairer, S. P. NArsett, and G. Wanner, Solving Ordinary Differential Equations I, Berlin, 1993.

  41. W. Zhang, H. Su, F. Zhu, and S. P. Bhattacharyya, “Improved exponential observer design for one-sided lipschitz nonlinear systems,” International Journal of Robust and Nonlinear Control, vol. 26, pp. 3958–3973, December 2016.

    MathSciNet  MATH  Google Scholar 

  42. W. Zhang, H. Su, H. Wang, and Z. Han, “Full-order and reduced-order observers for one-sided Lipschitz nonlinear systems using Riccati equations,” Communications in Nonlinear Science and Numerical Simulation, vol. 17, no. 12, pp. 4968–4977, December 2012.

    MathSciNet  MATH  Google Scholar 

  43. W. Zhang, H. Su, F. Zhu, and G. M. Azar, “Unknown input observer design for one-sided Lipschitz nonlinear systems,” Nonlinear Dynamics, vol. 79, no. 2, pp. 1469–1479, January 2015.

    MathSciNet  MATH  Google Scholar 

  44. Z. Ding, “Consensus disturbance rejection with disturbance observers,” IEEE Trans. on Industrial Electronics, vol. 62, no. 9, pp. 5829–5837, September 2015.

    Google Scholar 

  45. J. Hu, P. Bhowmick, and A. Lanzon, “Distributed adaptive time-varying group formation tracking for multi-agent systems with multiple leaders on directed graphs,” IEEE Trans. on Control of Netework Systems, vol. 7, no. 1, pp. 140–150, March 2020.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wei Zhang.

Additional information

Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Recommended by Associate Editor Yang Tang under the direction of Editor Hamid Reza Karimi. This work is supported by National Natural Science Foundation (NNSF) of China under Grant No. 61803256.

Chenhang Yan received his B.S. degree from the School of Mechanical Engineering, Taizhou University, Zhejiang, China, in 2018. He is currently pursuing an M.S. degree in the School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, China. His research interests include formation control, networked dynamical systems and adaptive control.

Wei Zhang received his B.S. and M.S. degrees from the University of Electronic Science and Technology of China, Chengdu, China, in 1999 and 2005, respectively, and a Ph.D. degree from Shanghai Jiao Tong University, Shanghai, China, in 2010. From 2015 to 2016, he was a Senior Visiting Scholar with the Texas A&M University, College Station, TX, USA. Since 2019, he has been a full Professor with the School of Mechnical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai. His current research interests include nonlinear control and observation, complex network, and multiagent coordination control. Prof. Zhang was a Guest Editor of Mathematical Problems in Engineering.

Xiaohang Li received her M.S. and Ph.D. degrees in control theory and control engineering from Tongji University, Shanghai, China, in 2016. She is currently an Associate Professor with the Shanghai University of Engineering Science, Shanghai. Her current research interests include observer design, model-based fault detection, and fault tolerant control.

Yuchen Qian received his B.S. degree in engineering from the School of Mechanical Engineering, Nanjing University of Science and Technology Zijin College, Nanjing, China, in 2017. He is currently pursuing an M.S. degree in mechanical and electronic engineering with the School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai, China. His current research interests include observation as well as consensus and formation control.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yan, C., Zhang, W., Li, X. et al. Observer-based Time-varying Formation Tracking for One-sided Lipschitz Nonlinear Systems via Adaptive Protocol. Int. J. Control Autom. Syst. 18, 2753–2764 (2020). https://doi.org/10.1007/s12555-019-0884-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12555-019-0884-9

Keywords

Navigation