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• W2616992174 abstract "In this work, we formulate a new approach to simultaneous constrained model predictive control and identification (MPCI). The proposed approach relies on the development of a persistent excitation (PE) criterion for processes described by DARX models. That PE criterion is used as an additional constraint in the standard on-line optimization of MPC. The resulting on-line optimization problem of MPCI is handled by successively solving a series of semi-definite programming problems. Advantages of MPCI in comparison to other closed-loop identification methods are (a) Constraints on process inputs and outputs are handled explicitly, (b) Deterioration of output regulation is kept to a minimum, while closed-loop identification is performed. The applicability of the method is illustrated by a number of simulation studies. Theoretical and computational issues for further investigation are suggested." @default.
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• W2616992174 date "1998-12-01" @default.
• W2616992174 modified "2023-10-12" @default.
• W2616992174 title "Simultaneous Constrained Model Predictive Control and Identification of DARX Processes" @default.
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• W2616992174 doi "https://doi.org/10.1016/s0005-1098(98)80005-8" @default.
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