BIBO stability of an adaptive time-frequency iterative learning control with application to microscale robotic deposition

Abstract

Microscale robotic deposition (/spl mu/-RD) is an emerging solid free-form manufacturing technique for construction of parts with microscale feature sizes. Part quality in this process is directly related to the robot tracking performance. In this paper an adaptive iterative learning control algorithm using a time-varying Q-filter is presented for robust high performance tracking control of the /spl mu/-RD robot. Using a switched systems analysis, the existence of a minimum dwell time for BIBO stability is demonstrated. Experimental results show the ability of the adaptive algorithm to stably improve performance over the initial fixed filter. The development of multi-ink valves allows construction of parts with multiple materials interlaced throughout and a sample two-ink manufactured part is presented.