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Springer Nonlinear Predictive Control Using Wiener Models - Springer

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Description

This comprehensive volume from Springer explores computationally efficient approaches to nonlinear predictive control through Wiener models, addressing both polynomial and neural network structures. Part of the Studies in Systems, Decision and Control series (volume 389), the book provides advanced methodologies for engineers and researchers working with complex control systems. The focus on computational efficiency makes these predictive control techniques practical for real-world applications where computational resources are limited. Ideal for postgraduate students, academic researchers, and industrial practitioners seeking to understand and implement Wiener model-based predictive control strategies that balance accuracy with computational demands.

Key Features

Covers computationally efficient approaches to nonlinear predictive control using Wiener model structures.

Addresses both polynomial and neural network implementations of Wiener models for control applications.

Published by Springer as part of the Studies in Systems, Decision and Control series volume 389.

Provides practical methodologies suitable for engineers developing advanced control systems.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
23 September 2022
Listed Since
26 August 2022

Barcode

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