Power Line Communication with Network Transmission Data Loss Based on Learning Control
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This paper proposed power line communication with transmission data. An iterative learning control method for the power line communication is studied by P-type learning control law. The data packet loss described as a stochastic Bernoulli process. The sufficient conditions are given for the convergence of the proposed algorithm by using the compression mapping method and norm theory. The convergence analysis guarantee the convergence of the tracking error in the sense of the \(\uplambda\)-norm. Finally, numerical simulations illustrate to verify the effectiveness of the proposed learning algorithm.
KeywordsIterative learning control Nonlinear system Networked control systems Data dropouts
The work was supported by the Hechi University Foundation (XJ2016ZD004), Hechi university Youth teacher Foundation (XJ2017QN08), the Projection of Environment Master Foundation (2017HJA001, 2017HJB001), The important project of the New Century Teaching Reform Project in Guangxi (2010JGZ033), Guangxi Youth teacher Foundation (2018KY0459).
All authors contributed equally and significantly in writing this article. All authors read and approved the final manuscript. Mengji Chen is corresponding author.
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Conflict of interests
The authors declare that there is no conflict of interests regarding the publication of this paper.
- 6.R. H. Chi, Z. S. Hou and S. L. Sui, Non-parameter adaptive iterative learning control for the freeway traffic ramp metering, Control Theory & Applications, Vol. 25, No. 6, pp. 1011–1015, 2008.Google Scholar
- 15.H. Li, Z. Sun and F. Sun, Networked control systems: an overview of state-of-the-art and the prospect in future research, Control Theory & Applications, Vol. 27, No. 2, pp. 238–243, 2010.Google Scholar
- 16.H. S. Ahn, Y. Q. Chen, K. L. Moore, Discrete time intermittent iterative learning control with independent data dropouts, Proceedings of the 17th lFAC World Congress. Korea: IFAC, pp. 12442–12447, 2008.Google Scholar
- 19.H. Yao, Mean square exponential stability control of uncertain discrete network based on stochastic time delay and data loss, Process Automation Committee of China Association of Automation. The 28th China Process Control Conference (CPCC 2017) and China Conference on Process Control 30th Anniversary Abstract Collection. China Association for Automation Process Control Professional Committee, p. 1, 2017.Google Scholar
- 20.Y. Yang, J. Zhu, J. Wei and H. X. Xu, Research on carrier routing based on ant colony genetic hybrid, Ningxia Electric Power, Vol. 4, pp. 52–57, 2017.Google Scholar
- 21.X. Liu, J. Liu, H. Sun, H. Liu and X. Gu, OFDM timing synchronization algorithm for power line communication system, Electric Power Automation Equipment, Vol. 38, No. 01, pp. 179–183, 2018.Google Scholar
- 22.Q. Guo, W. Zhong, H. Zhang, H. Zhang, R. Yu, Adaptive rate control of heterogeneous communication network in smart grid, Journal of South China Normal University (Natural Science Edition) (05)[2018-03-25], 2018.Google Scholar
- 25.J. Liu, X. E. Ruan, Networked iterative learning control for linear-time-invariant systems with random packet losses, Proceeding of the 35th Chinese Control Conference, Chendu, China, pp. 38–43, 2016.Google Scholar