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- W2108431054 abstract "Models are extensively used in the design and implementation of advanced process control systems. In model predictive control (MPC), model of the plant is used to predict the future output of the plant using the current and future optimal inputs and past outputs. Therefore, the design of MPC, essentially, includes the development of an effective plant model that can be used for predicting the future output of the plant with good accuracy (Camacho & Bordon, 2004; Rawlings, 2000). Models can be developed either from purely theoretical analysis (conservation principles, thermodynamics, etc.) or from experimental data or somewhere in between. The process of model development from experimental data is known as system identification. The identification test can be conducted either in open-loop (open-loop identification) or while the plant is under feedback control (closed-loop identification)." @default.
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- W2108431054 date "2010-10-15" @default.
- W2108431054 modified "2023-09-27" @default.
- W2108431054 title "System Identification using Orthonormal Basis Filters" @default.
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- W2108431054 doi "https://doi.org/10.3923/jas.2010.2516.2522" @default.
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