Different intelligent robust control schemes for precise positioning system

This paper presents the design of two different H ∞ robust controllers for a single axis positioning system via two different schemes; The 2 H ∞ robust controller, which is suitable for accurate tracking performance and an integrator-H ∞ robust controller which can also be tuned for accurate trackin...

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Bibliographic Details
Main Authors: Raafat, Safanah M, Akmeliawati, Rini, Martono, Wahyudi
Format: Conference Proceeding
Language:English
Subjects:
Adaptive neural fuzzy inference system
Bandwidth
Control systems
Data models
H
Mathematical model
Robust control
Robustness
single axis positioning system
uncertainties
Uncertainty
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Summary:This paper presents the design of two different H ∞ robust controllers for a single axis positioning system via two different schemes; The 2 H ∞ robust controller, which is suitable for accurate tracking performance and an integrator-H ∞ robust controller which can also be tuned for accurate tracking. However, each approach has some certain features that need to be investigated for the application under study. Adaptive neural fuzzy inference system is utilized in both schemes to develop a non-conservative accurate uncertainty weighting function. Both methods can achieve wide bandwidth, high resolution, improved tracking performance, and robustness to modelling uncertainties, as will be demonstrated in the experimental results.
DOI:10.1109/ICSGRC.2010.5562532