학술논문
Adaptive Iterative Learning Control for Industry Batch Process with Time-Varying and Unknown Parameters
Document Type
Conference
Author
Source
2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS) Data Driven Control and Learning Systems Conference (DDCLS), 2023 IEEE 12th. :406-410 May, 2023
Subject
Language
ISSN
2767-9861
Abstract
The batch process is a typical manufacturing mode in industry. In this article, an adaptive ILC method is proposed for the batch process with time-varying and unknown parameters. The proposed method involves merging an adaptive updating law that utilizes the steepest descent method to estimate unknown parameters with a controller that adjusts the estimated system. The proposed condition ensures that the estimated parameter error remains bounded and that the estimated state error is stabilized. The controller utilizes the estimated results to steer the estimated system to track the reference trajectory. A numerical experiment is presented to demonstrate the efficiency of the proposed method.