A study of integrated experiment design for NMPC applied to the Droop model

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• 作者：D. Telen^a ; B. Houska^b ; M. Vallerio^a ; F. Logist^a ; J. Van Impe^a ; ^{jan.vanimpe@cit.kuleuven.be}
• 关键词：Nonlinear model predictive control ; Integrated experiment design ; Economic optimal experiment design ; Nonlinear matrix inequality ; Droop model
• 刊名：Chemical Engineering Science
• 出版年：2017
• 出版时间：16 March 2017
• 年：2017
• 卷：160
• 期：Complete
• 页码：370-383
• 全文大小：1022 K
• 卷排序：160

文摘

Two techniques for integration experiment design in NMPC. First technique results in nonlinear matrix inequality (NLMI). NMLI is tackled by Sylvester's criterion allowing implementation in existing tools. Second technique uses the notion of economic experiment design. Single scalar constraint is obtained representing the predicted economic loss.