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author:

Ning, Zhou (Ning, Zhou.) [1] | Riqing, Chen (Riqing, Chen.) [2] | Jie, Huang (Jie, Huang.) [3] (Scholars:黄捷) | Guoxing, Wen (Guoxing, Wen.) [4] | Sixing, Zhang (Sixing, Zhang.) [5]

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Abstract:

The problem of formation reconfiguration for multiple spacecraft is discussed in the presence of external disturbances. To achieve the H∞ performance, an elaborate formation task function is designed by using null-space based behavioral control method, then a predesigned desired velocity is calculated for each spacecraft. By employing variable structure technique associated with the universal approximation property of radial basis function neural networks (RBFNN), an adaptive H∞ coordination control scheme is proposed for each spacecraft to implement the specified formation task. Finally, rigorous theoretical analysis shows that the developed algorithm implements the formation reconfiguration task and satisfies the H∞ performance. © 2018 Technical Committee on Control Theory, Chinese Association of Automation.

Keyword:

Adaptive control systems Radial basis function networks Spacecraft

Community:

  • [ 1 ] [Ning, Zhou]College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou; 350002, China
  • [ 2 ] [Ning, Zhou]Faculty of Science and Engineering, University of Groningen, Groningen; 9747AG, Netherlands
  • [ 3 ] [Riqing, Chen]College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou; 350002, China
  • [ 4 ] [Jie, Huang]Faculty of Science and Engineering, University of Groningen, Groningen; 9747AG, Netherlands
  • [ 5 ] [Jie, Huang]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 6 ] [Guoxing, Wen]College of Science, Binzhou University, Binzhou, Shandong; 256600, China
  • [ 7 ] [Sixing, Zhang]School of Automation, Beijing Institute of Technology, Beijing; 100081, China

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ISSN: 1934-1768

Year: 2018

Volume: 2018-July

Page: 2939-2943

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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