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- W2618114562 abstract "Abstract This paper proposes an approach for the design of discrete-time decentralized control systems covering not only the case of m-step delay sharing information pattern, but also any general nonclassical information pattern where the non-local information is not spread among the subsystems. It employs the model-based predictive control (MBPC) scheme combined with fuzzy prediction for the interconnections among the subsystems. A state space model is used at each control station to predict the corresponding subsystem output over a long-range time period. The interaction trajectories are considered to be non-linear functions of the states of the subsystems. In all cases, the interconnections and the necessary predictions for them are estimated by an appropriate neuro-fuzzy identifier trained on-line using the back-propagation training algorithm. Representative computer simulation results are provided and compared for nontrivial example systems." @default.
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- W2618114562 date "1998-06-01" @default.
- W2618114562 modified "2023-09-26" @default.
- W2618114562 title "Decentralized Predictive Control of Large Scale Systems Using Neuro-Fuzzy Identifiers for their Interconnections" @default.
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- W2618114562 doi "https://doi.org/10.1016/s1474-6670(17)36038-x" @default.
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