Iterative learning control for discrete-time systems with quantised measurements

作者：Bu Xuhui^*; Wang Taihua; Hou Zhongsheng; Chi Ronghu

来源：IET Control Theory and Applications, 2015, 9(9): 1455-1460.

DOI：10.1049/iet-cta.2014.1056

• NETWORKED CONTROL-SYSTEMS
• NONLINEAR-SYSTEMS
• LINEAR-SYSTEMS
• FEEDBACK STABILIZATION
• MULTIAGENT SYSTEMS
• RELATIVE DEGREE
• CONTROL DESIGN
• DATA DROPOUTS
• STATE

In this study, the problem of iterative learning control (ILC) for discrete-time systems with quantised output measurements is considered. Here, a logarithmic quantiser is introduced and an ILC scheme is constructed by using output signals with only a finite number of quantisation levels. By using sector bound method to deal with the quantisation error, a learning condition of ILC that guarantees the convergence of tracking error is derived through rigorous analysis. It is shown that the convergence condition is determined by quantisation level, and the tracking error converges to a bound depending on quantisation density. Furthermore, the extension from linear systems to non-linear systems is also addressed. Finally, two illustrative examples are presented to demonstrate the theoretical results for both linear and non-linear systems.

• 出版日期2015-6-6
• 单位青岛科技大学; 河南理工大学; 北京交通大学