Enhanced servo performance of a single axis positioning system in an intelligent robust framework

This paper proposes an optimized performance of an intelligent H
_∞
robust controller of a single axis positioning system. The objective is to achieve wider bandwidth, better resolution, and robustness to modeling uncertainties. The main contribution is the combination of intelligent uncertainty weighting function and optimized weighting function in an H
_∞
robust controller design. The main distinguishing features of this approach are: the accurate, fast identification of the uncertainty bounds using an adaptive neuro fuzzy inference system and the automatic tuning of the performance weighting function in accordance to performance requirements. v-gap measure is utilized to validate the intelligent identified uncertainty bounds for wider stability region. Then the methodology is demonstrated through both simulation and experiments on the practical system. Experimental results also demonstrate the robustness against load variations.