Super-Twisting Sliding Mode Control for Markovian Jump Systems Based on Quantized Output-Feedback

• 成果类型: Article
• 署名作者: Huang, Zixin; Zhou, Sai; Song, Jun; Shu, Zhan
• 署名单位: Wuhan Institute of Technology; Xi'an Jiaotong University; Anhui University; University of Alberta
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2025.3647572
• 发表日期: 2026
• 关键词: linear-systems; algorithm

摘要

This article focused on designing the super-twisting algorithm (STA)-based output-feedback sliding mode control (SMC) for multi-input Markovian jump systems under digital channel transmission. Specifically, the uniform quantization strategy is employed to implement the network communication for both the measured outputs and the sliding variables. It is shown that the novel quantized-data-based output-feedback STA can guarantee the practical reachability of the sliding variable with probability one by means of a dynamic adjustment policy for quantizers' parameters. Sufficient conditions for the existence of the feasible STA parameters and output-feedback SMC gains are proposed in terms of nonconvex equalities and inequalities, which can be solved effectively via a modified genetic algorithm combining the gridding search technique. Finally, a numerical example is provided to verify the effectiveness of the proposed STA-based SMC scheme for Markovian jump system via quantized output-feedback.