2021/08/16 by Maxwell Wu, Mitchell Cobb, Wu, Maxwell +9
Engineering · #Advanced Numerical Analysis Techniques #Advanced machining processes and optimization #FOS: Electrical engineering #Iterative Learning Control Systems #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2108.06866
openalex publication_date 2021/08/16 · openalex created_date 2021/08/30 · openalex updated_date 2026/07/28
This paper presents an iterative learning control (ILC) scheme for continuously operated repetitive systems for which no initial condition reset exists. To accomplish this, we develop a lifted system representation that accounts for the effect of the initial conditions on dynamics and projects the dynamics over multiple future iterations. Additionally, we develop an economic cost function and update law that considers the performance over multiple iterations in the future, thus allowing for the prediction horizon to be larger than just the next iteration. Convergence of the iteration varying initial condition and applied input are proven and demonstrated using a simulated servo-positioning system test case.