Advanced Motion Control for Precision Mechatronics: Control, Identification, and Learning of Complex Systems

Abstract

Wafer scanners, printers, microscopes, and medical imaging scanners are examples of scientific and manufacturing devices 
that need precise and quick movements. A rise in these demands calls for improved control performance. This paper's goal 
is to list a number of advanced motion control issues brought on by these growing demands for precision, speed, and cost. 
For example, overactuation, oversensing, inferential control, and position-dependent control must be used to explicitly 
address flexible mechanics. This in turn necessitates adequate models with the right amount of complexity. Finding and 
learning models and controllers from experimental data is made possible by the low cost of testing and gathering vast 
volumes of precise data, which is one of the key benefits of such motion systems. The article describes a number of current 
advancements that make up a comprehensive framework for the identification, control, and learning of complicated motion 
systems. This might thus open the door for new mechatronic design ideas, which could result in fast, light machines with 
improved motion control that explicitly compensates for spatiotemporal flexible mechanics.