Title :
Different intelligent robust control schemes for precise positioning system
Author :
Raafat, Safanah M. ; Akmeliawati, Rini ; Martono, Wahyudi
Author_Institution :
Mechatron. Eng. Dept., Int. Islamic Univ. Malaysia, Kuala-Lumpur, Malaysia
Abstract :
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.
Keywords :
H∞ control; adaptive systems; fuzzy control; fuzzy neural nets; inference mechanisms; neurocontrollers; position control; robust control; tracking; uncertainty handling; adaptive neural fuzzy inference system; integrator H∞ robust control; intelligent robust control; nonconservative uncertainty weighting function; single axis positioning system; tracking system; Bandwidth; Control systems; Data models; Mathematical model; Robust control; Robustness; Uncertainty; Adaptive neural fuzzy inference system; H∞; single axis positioning system; uncertainties;
Conference_Titel :
Control and System Graduate Research Colloquium (ICSGRC). 2010 IEEE
Conference_Location :
Shah Alam
Print_ISBN :
978-1-4244-7238-3
DOI :
10.1109/ICSGRC.2010.5562532