Constrained Iterative Learning Control for Linear Time-Varying Systems With Experimental Validation on a High-Speed Rack Feeder
Bing Chu, Andreas Rauh, Harald Aschemann, Eric Rogers, D.H. Owens
Abstract
Iterative learning control (ILC) applies to systems required to track the desired trajectory of finite duration repeatedly. This article considers constrained ILC design for linear time-varying systems, a problem with limited, in relative terms, results in the literature but not uncommon in practical applications. Different design algorithms are developed, and their convergence properties are established. An extension of these designs to point-to-point tracking tasks is given. A high-speed rack feeder typically used in automated warehouses is considered to verify the designs. It represents a flexible beam structure subject to kinematic constraints, such as a maximum velocity and a maximum acceleration with a vertically moving mass causing the time-varying characteristics. Experimental results demonstrate the effectiveness of the designs.