离散二维马尔可夫切换系统的SMC:遗传算法

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-10-31 DOI:10.1002/rnc.7702
Shaowei Li, Wenhai Qi, Ju H. Park, Jun Cheng, Kaibo Shi
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引用次数: 0

摘要

针对具有Roesser模型的离散二维马尔可夫切换系统,提出了基于遗传算法的滑模控制策略。利用常见的二维滑动面,设计了底层系统的二维SMC律。根据Lyapunov稳定性准则,建立了二维马尔可夫切换系统的渐近均方稳定性的充分条件,并保证了滑动区域的可达性。利用迭代优化算法,构造了一种有效的遗传算法SMC策略,通过搜索理想的滑动增益来最小化滑动区域。最后,通过实例验证了所提二维SMC策略的适用性。
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SMC for Discrete 2-D Markov Switching Systems: Genetic Algorithm

The sliding mode control (SMC) strategy based on genetic algorithm is proposed for discrete two-dimensional (2-D) Markov switching systems with the Roesser model. By means of common 2-D sliding surface, the 2-D SMC law is designed for the underlying system. According to Lyapunov stability criteria, sufficient conditions are established for the asymptotic mean-square stability of the underlying 2-D Markov switching systems and the reachability of the sliding region is guaranteed. Utilizing an iteration optimizing algorithm, an effective SMC strategy under genetic algorithm is constructed to minimize the sliding region by searching an ideal sliding gain. Finally, the applicability of the proposed 2-D SMC strategy is verified through an example.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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