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This monograph introduces the authors¿ work on model predictive control system design using extended state space and extended non-minimal state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control algorithms, the extension to predictive functional control, constrained control, closed-loop system analysis, model predictive control optimization-based PID control, genetic algorithm optimization-based model predictive control, and industrial applications. Providing important insights, useful methods and practical algorithms that can be used in chemical process control and optimization, it offers a valuable resource for researchers, scientists and engineers in the field of process system engineering and control engineering.
| Autorius: | Ridong Zhang, Furong Gao, Anke Xue, |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2018 |
| Knygos puslapių skaičius: | 156 |
| ISBN-10: | 9811343268 |
| ISBN-13: | 9789811343261 |
| Formatas: | 235 x 155 x 9 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Model Predictive Control: Approaches Based on the Extended State Space Model and Extended Non-minimal State Space Model“
