Iterative learning control for networked stochastic systems with random packet losses

Abstract

The iterative learning control is constructed for discrete-time stochastic systems with random measurement losses modelled by a stochastic sequence. A simple P-type update law is used and the almost sure convergence is strictly proved for both linear case and nonlinear case based on stochastic approximation. Illustrative examples show the effectiveness of the proposed approach.

Keywords:

• iterative learning control
• networked stochastic system
• random packet losses
• stochastic approximation

Additional information

Funding

This work was supported by National Natural Science Foundation of China (61304085,61374099), Beijing Natural Science Foundation (4152040), the Fundamental Research Funds for the Central Universities (ZY1318), and Beijing Higher Education Young Elite Teacher Project (YETP0505).