四阶偏微分多智能体系统的迭代学习控制

Abstract

Abstract:

In this paper, the problem of iterative learning control for multi-agent systems is studied based on consensus. All the considered agents are constructed by the fourth-order beam equations. Based on the network topology, a consensus iterative learning control protocol is designed by using the information of adjacent agents. When the iterative learning law is applied to the systems, the consensus errors are bounded, and furthermore, the consensus errors on ${L^2}$ space tend to zero as the iteration index tends to infinity in the absence of initial errors. The effectiveness of the algorithm is verified by simulation examples.

Key words: Multi-agent systems, Iterative learning control protocol, Fourth-order beam equation, L² space

CLC Number:

TP13

Pengfei Yu,Qin Fu. Iterative Learning Control for Fourth Order Partial Differential Multi-Agent Systems[J].Acta mathematica scientia,Series A, 2020, 40(4): 1029-1042.

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References

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[1]	Dan Zhang,Qin Fu,Zhenjie Chen. Containment Control for Partial Differential Multi-Agent Systems via Iterative Learning Algorithm [J]. Acta mathematica scientia,Series A, 2021, 41(4): 1111-1123.
[2]	Ge Yanrong, Qi Yaohui, Chen Yangzhou, Song Xuejun. Consensus of High-Order Discrete-Time Multi-Agent Systems with Quantized Information [J]. Acta mathematica scientia,Series A, 2017, 37(6): 1176-1188.

Iterative Learning Control for Fourth Order Partial Differential Multi-Agent Systems

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