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  • 标题:Encrypted cloud-based MPC for linear systems with input constraints
  • 本地全文:下载
  • 作者:Moritz Schulze Darup ; Adrian Redder ; Daniel E. Quevedo
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2018
  • 卷号:51
  • 期号:20
  • 页码:535-542
  • DOI:10.1016/j.ifacol.2018.11.035
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractWe present a novel cloud-based MPC scheme that is based on a recently proposed real-time proximal gradient method. The cloud-based implementation requires sensitive data (e.g., system states) to be transmitted via public networks and to be processed in the cloud. We guarantee privacy of the data throughout the control-loop by encrypting the control scheme using (partial) homomorphic encryption. The resulting encrypted MPC computes encrypted predictive control actions based on encrypted system states (without intermediate decryptions).
  • 关键词:Keywordslinear systemsinput constraintspredictive controlproximal gradient methodsreal-time iterationscloud-based controlencrypted controlhomomorphic encryption
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