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Control Using Inverse Model Algorithms

Chapter
Part of the Advances in Industrial Control book series (AIC)

Abstract

Inverse model based algorithms form the basis of Iterative Learning Control and provide many of the underlying techniques and relationships that appear in or motivate other algorithms. The chapter provides a systematic approach to the design problem and the robustness of schemes based on the use of left or right inverse systems. Frequency domain conditions for MIMO discrete state space systems are derived in detail.

Keywords

Modelling Error Inverse Model State Space Model Iterative Learn Control Inverse System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  1. 1.University of SheffieldSheffieldUK

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