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- W4381481446 abstract "Model Predictive Control (MPC) is widely recognized as an important control strategy in both practical and theoretical frameworks. Indeed, as it is informed in the Bibliography notes, it has been successfully applied to many systems of practical importance. One of the main reasons for that success is the fact that MPC is able to cope with state and control variable constraints. Hence, our main purpose is to generalize the previous state feedback design procedures in order to incorporate the mentioned constraints keeping unchanged the convex nature of the problems we need to solve. Of course, questions involving closed-loop system feasibility, stability, and robustness that naturally arise are tackled and adequately answered. The computational burden involved, for solving the control design conditions for systems of moderate order, is not prohibitive, making their calculation and online implementation possible in many instances." @default.
- W4381481446 created "2023-06-22" @default.
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- W4381481446 date "2023-01-01" @default.
- W4381481446 modified "2023-10-01" @default.
- W4381481446 title "Model Predictive Control" @default.
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- W4381481446 doi "https://doi.org/10.1007/978-3-031-29754-0_8" @default.
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