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Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures - Studies in Systems, Decision and Control Maciej Lawrynczuk 2022 edition
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Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures - Studies in Systems, Decision and Control
Maciej Lawrynczuk
The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances.
343 pages, 121 Illustrations, color; 46 Illustrations, black and white; XXIII, 343 p. 167 illus., 12
| Media | Books Paperback Book (Book with soft cover and glued back) |
| Released | September 23, 2022 |
| ISBN13 | 9783030838171 |
| Publishers | Springer Nature Switzerland AG |
| Pages | 343 |
| Dimensions | 150 × 220 × 10 mm · 563 g |
| Language | German |
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