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Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures

Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures

Paperback

Series: Studies in Systems, Decision and Control, Book 389

Technology & Engineering

ISBN10: 303083817X
ISBN13: 9783030838171
Publisher: Springer
Published: Sep 23 2022
Pages: 343
Weight: 1.13
Height: 0.76 Width: 6.14 Depth: 9.21
Language: English
This book presents computationally efficient MPC solutions. 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. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant.

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