August & September  2019, 12(4&5): 727-734. doi: 10.3934/dcdss.2019047

Design of one type of linear network prediction controller for multi-agent system

School of Information Engineering, Wuyi University, Guangdong, Jiangmen 529020, China

* Corresponding author: Hong Man

Received  June 2017 Revised  October 2017 Published  November 2018

In this paper, to solve network delay and network tracking control problems in multi-agent system communication, a design method of network prediction controller was introduced based on state difference estimation and output tracking error. This design method not only effectively compensates for influences of network delay on the system but also ensures stability of the closed-loop system and realizes the same tracking performance among multi-agents. The effectiveness of the proposed method was proven by simulation experiment.The key innovation in the paper is that the influence of network delay on the system was actively compensated and a network prediction tracking control mechanism was proposed to guarantee the stability of the closed-loop system.The proposed method achieved the same tracking with the local tracking control system under certain conditions.

Citation: Hong Man, Yibin Yu, Yuebang He, Hui Huang. Design of one type of linear network prediction controller for multi-agent system. Discrete and Continuous Dynamical Systems - S, 2019, 12 (4&5) : 727-734. doi: 10.3934/dcdss.2019047
References:
[1]

H. Gao and T. Chen, Network-based $H_{∞ } $ output tracking control, IEEE Transactions on Automatic Control, 53 (2008), 655-667.  doi: 10.1109/TAC.2008.919850.

[2]

Y. Guo, Q. Zhang and D. Gong, et al., Robust fault-tolerant control of networked control systems with time-varying delays, Control and Decision, 23 (2008), 689-692, 696.

[3]

W. P. M. H. Heemels, R. Merry and T. Oomen, Alternative frequency-domain stability criteria for discrete-time networked systems with multiple delays, The 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems, Annecy, France: IFAC, (2010), 73-78.

[4]

S. H. Hong, Scheduling algorithm of data sampling times in the integrated communication and control systems, IEEE Transactions on Control Systems Technology, 3 (1995), 225-230. 

[5]

P. Li and J. Lam, Decentralized control of compartmental networks with $H_{∞ } $ tracking performance, IEEE Transactions on Industrial Electronics, 60 (2013), 546-553. 

[6]

D. Liberzon, Switching in Systems and Control, Boston, MA: Birkhauser, 2003. doi: 10.1007/978-1-4612-0017-8.

[7]

G. P. Liu, J. X. Mu and D. Rees, et al., Design and stability analysis of networked control systems with random communication time delay using the modified MPC, International Journal of Control, 79 (2006), 288-297. doi: 10.1080/00207170500533288.

[8]

L. Lu, S. Zhu and J. Meng, et al., Predictive control applied queuing strategy in networked control systems, The 1st IEEE Conference on Industrial Electronics and Applications, Singapore: IEEE, (2006), 73-78.

[9]

D. Ma and J. Zhao, Modeling and stability analysis based on hybrid system technology for networked control systems, Journal of Nort Heastern University(Nat Ural Science), 26 (2005), 817-820. 

[10]

B. TangG. P. Liu and W. H. Gui, Improvement of state feedback controller design for networked control systems, IEEE Transactions on Circuits and Systems Ⅱ: Express Briefs, 55 (2008), 464-468. 

[11]

Y. L. Wang and G. H. Yang, Robust $H_{∞ } $ model reference tracking control for networked control systems with communication constraints, International Journal of Control, Automation and Systems, 7 (2009), 992-1000. 

[12]

H. ZhangY. Shi and M. Liu, $H_{∞ } $ step tracking control for networked discrete-time nonlinear systems with integral and predictive actions, IEEE Transactions on Industrial Electronics, 9 (2013), 337-345. 

[13]

H. ZhaoM. Wu and G. Liu, A controller design method for networked control systems with time-varying delays, Information and Control, 35 (2006), 325-328. 

show all references

References:
[1]

H. Gao and T. Chen, Network-based $H_{∞ } $ output tracking control, IEEE Transactions on Automatic Control, 53 (2008), 655-667.  doi: 10.1109/TAC.2008.919850.

[2]

Y. Guo, Q. Zhang and D. Gong, et al., Robust fault-tolerant control of networked control systems with time-varying delays, Control and Decision, 23 (2008), 689-692, 696.

[3]

W. P. M. H. Heemels, R. Merry and T. Oomen, Alternative frequency-domain stability criteria for discrete-time networked systems with multiple delays, The 2nd IFAC Workshop on Distributed Estimation and Control in Networked Systems, Annecy, France: IFAC, (2010), 73-78.

[4]

S. H. Hong, Scheduling algorithm of data sampling times in the integrated communication and control systems, IEEE Transactions on Control Systems Technology, 3 (1995), 225-230. 

[5]

P. Li and J. Lam, Decentralized control of compartmental networks with $H_{∞ } $ tracking performance, IEEE Transactions on Industrial Electronics, 60 (2013), 546-553. 

[6]

D. Liberzon, Switching in Systems and Control, Boston, MA: Birkhauser, 2003. doi: 10.1007/978-1-4612-0017-8.

[7]

G. P. Liu, J. X. Mu and D. Rees, et al., Design and stability analysis of networked control systems with random communication time delay using the modified MPC, International Journal of Control, 79 (2006), 288-297. doi: 10.1080/00207170500533288.

[8]

L. Lu, S. Zhu and J. Meng, et al., Predictive control applied queuing strategy in networked control systems, The 1st IEEE Conference on Industrial Electronics and Applications, Singapore: IEEE, (2006), 73-78.

[9]

D. Ma and J. Zhao, Modeling and stability analysis based on hybrid system technology for networked control systems, Journal of Nort Heastern University(Nat Ural Science), 26 (2005), 817-820. 

[10]

B. TangG. P. Liu and W. H. Gui, Improvement of state feedback controller design for networked control systems, IEEE Transactions on Circuits and Systems Ⅱ: Express Briefs, 55 (2008), 464-468. 

[11]

Y. L. Wang and G. H. Yang, Robust $H_{∞ } $ model reference tracking control for networked control systems with communication constraints, International Journal of Control, Automation and Systems, 7 (2009), 992-1000. 

[12]

H. ZhangY. Shi and M. Liu, $H_{∞ } $ step tracking control for networked discrete-time nonlinear systems with integral and predictive actions, IEEE Transactions on Industrial Electronics, 9 (2013), 337-345. 

[13]

H. ZhaoM. Wu and G. Liu, A controller design method for networked control systems with time-varying delays, Information and Control, 35 (2006), 325-328. 

Figure 1.  Structure of the Network Prediction Tracking Control System
Figure 2.  Network tracking control without prediction tracking mechanism
Figure 3.  Network prediction tracking control
[1]

Giulia Cavagnari, Antonio Marigonda, Benedetto Piccoli. Optimal synchronization problem for a multi-agent system. Networks and Heterogeneous Media, 2017, 12 (2) : 277-295. doi: 10.3934/nhm.2017012

[2]

Zhiyong Sun, Toshiharu Sugie. Identification of Hessian matrix in distributed gradient-based multi-agent coordination control systems. Numerical Algebra, Control and Optimization, 2019, 9 (3) : 297-318. doi: 10.3934/naco.2019020

[3]

Rui Li, Yingjing Shi. Finite-time optimal consensus control for second-order multi-agent systems. Journal of Industrial and Management Optimization, 2014, 10 (3) : 929-943. doi: 10.3934/jimo.2014.10.929

[4]

Hongru Ren, Shubo Li, Changxin Lu. Event-triggered adaptive fault-tolerant control for multi-agent systems with unknown disturbances. Discrete and Continuous Dynamical Systems - S, 2021, 14 (4) : 1395-1414. doi: 10.3934/dcdss.2020379

[5]

Seung-Yeal Ha, Dohyun Kim, Jaeseung Lee, Se Eun Noh. Emergent dynamics of an orientation flocking model for multi-agent system. Discrete and Continuous Dynamical Systems, 2020, 40 (4) : 2037-2060. doi: 10.3934/dcds.2020105

[6]

Richard Carney, Monique Chyba, Chris Gray, George Wilkens, Corey Shanbrom. Multi-agent systems for quadcopters. Journal of Geometric Mechanics, 2022, 14 (1) : 1-28. doi: 10.3934/jgm.2021005

[7]

Shruti Agarwal, Gilles Carbou, Stéphane Labbé, Christophe Prieur. Control of a network of magnetic ellipsoidal samples. Mathematical Control and Related Fields, 2011, 1 (2) : 129-147. doi: 10.3934/mcrf.2011.1.129

[8]

Zhongqiang Wu, Zongkui Xie. A multi-objective lion swarm optimization based on multi-agent. Journal of Industrial and Management Optimization, 2022  doi: 10.3934/jimo.2022001

[9]

Claus Kirchner, Michael Herty, Simone Göttlich, Axel Klar. Optimal control for continuous supply network models. Networks and Heterogeneous Media, 2006, 1 (4) : 675-688. doi: 10.3934/nhm.2006.1.675

[10]

Chao Chen, Shanlin Yi, Feng Wang, Chengxi Zhang, Qingmin Yu. Prescribed performance tracking control of multi-link robotic manipulator with uncertainties. Mathematical Foundations of Computing, 2022  doi: 10.3934/mfc.2022012

[11]

Nadia Loy, Andrea Tosin. Boltzmann-type equations for multi-agent systems with label switching. Kinetic and Related Models, 2021, 14 (5) : 867-894. doi: 10.3934/krm.2021027

[12]

Mei Luo, Jinrong Wang, Yumei Liao. Bounded consensus of double-integrator stochastic multi-agent systems. Discrete and Continuous Dynamical Systems - S, 2022  doi: 10.3934/dcdss.2022088

[13]

V. Lanza, D. Ambrosi, L. Preziosi. Exogenous control of vascular network formation in vitro: a mathematical model. Networks and Heterogeneous Media, 2006, 1 (4) : 621-637. doi: 10.3934/nhm.2006.1.621

[14]

Yinfei Li, Shuping Chen. Optimal traffic signal control for an $M\times N$ traffic network. Journal of Industrial and Management Optimization, 2008, 4 (4) : 661-672. doi: 10.3934/jimo.2008.4.661

[15]

Arti Mishra, Benjamin Ambrosio, Sunita Gakkhar, M. A. Aziz-Alaoui. A network model for control of dengue epidemic using sterile insect technique. Mathematical Biosciences & Engineering, 2018, 15 (2) : 441-460. doi: 10.3934/mbe.2018020

[16]

Brendan Pass. Multi-marginal optimal transport and multi-agent matching problems: Uniqueness and structure of solutions. Discrete and Continuous Dynamical Systems, 2014, 34 (4) : 1623-1639. doi: 10.3934/dcds.2014.34.1623

[17]

Tyrone E. Duncan. Some partially observed multi-agent linear exponential quadratic stochastic differential games. Evolution Equations and Control Theory, 2018, 7 (4) : 587-597. doi: 10.3934/eect.2018028

[18]

Xi Zhu, Meixia Li, Chunfa Li. Consensus in discrete-time multi-agent systems with uncertain topologies and random delays governed by a Markov chain. Discrete and Continuous Dynamical Systems - B, 2020, 25 (12) : 4535-4551. doi: 10.3934/dcdsb.2020111

[19]

Zhongkui Li, Zhisheng Duan, Guanrong Chen. Consensus of discrete-time linear multi-agent systems with observer-type protocols. Discrete and Continuous Dynamical Systems - B, 2011, 16 (2) : 489-505. doi: 10.3934/dcdsb.2011.16.489

[20]

Yibo Zhang, Jinfeng Gao, Jia Ren, Huijiao Wang. A type of new consensus protocol for two-dimension multi-agent systems. Numerical Algebra, Control and Optimization, 2017, 7 (3) : 345-357. doi: 10.3934/naco.2017022

2021 Impact Factor: 1.865

Metrics

  • PDF downloads (254)
  • HTML views (681)
  • Cited by (0)

Other articles
by authors

[Back to Top]