Title: Robust adaptive iterative learning control for nonlinear discrete-time system in fading environments with joint multiplicative-additive effects

Authors: Yunshan Wei; Chengxi Liang; Kai Wan; Xingfeng Cai; Xinru Liu

Addresses: School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, 510006, China; Key Laboratory of On-Chip Communication and Sensor Chip of Guangdong Higher Education Institutes, Guangzhou, 510006, China ' School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, 510006, China ' School of Electronic Information and Electronical Engineering, Huizhou University, Huizhou, 516067, China; The 25th Group of the CPC Central Committee's Organization Department Doctoral Service Corps for Tibetan Assistance, Lhasa, 850000, China ' School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, 510006, China ' School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, 510006, China

Abstract: This study investigates the robustness of discrete-time adaptive iterative learning control (AILC) under fading channels for nonlinear dynamical systems with multiplicative and additive channel noises. The output and the input fading channel are considered integral components of the system during the analysis process, and thus, the system is reconstructed. Each component of system outputs suffers different multiplicative noise. The framework jointly addresses stochastic multiplicative and additive randomness effects in signal propagation. The variable tracking targets and error dead zones is taken into account in AILC design. The robustness characteristics of the developed AILC methodology are systematically examined. The validity of the developed approach is confirmed through systematic numerical simulations.

Keywords: adaptive iterative learning control; fading channels; nonlinear discrete-time systems.

DOI: 10.1504/IJBIC.2026.153416

International Journal of Bio-Inspired Computation, 2026 Vol.27 No.3, pp.143 - 156

Received: 19 May 2025
Accepted: 10 Sep 2025
Published online: 07 May 2026 *

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