事件触发观测下时滞马尔科夫跳跃系统广义记忆滑模控制

杨玥; 黄佳男; 马宗方; 苏晓杰

doi:10.16383/j.aas.c240723

事件触发观测下时滞马尔科夫跳跃系统广义记忆滑模控制

doi: 10.16383/j.aas.c240723 cstr: 32138.14.j.aas.c240723

1.
西安建筑科技大学信息与控制工程学院西安 710311
2.
重庆大学自动化学院重庆 400044

基金项目: 国家自然科学基金(62306228, 62441237), 陕西省重点研发计划(2024GX-YBXM-132)资助

详细信息

作者简介:
杨玥：西安建筑科技大学信息与控制工程学院副教授. 2022年获得重庆大学控制理论与工程专业博士学位. 主要研究方向为智能无人系统的安全控制. 本文通信作者. E-mail: yangyue@xauat.edu.cn

黄佳男：西安建筑科技大学信息与控制工程学院硕士研究生. 主要研究方向为滑模控制, 模糊控制, 及其在机器人系统中的应用. E-mail: h_jn123@xauat.edu.cn

马宗方：西安建筑科技大学信息与控制工程学院教授. 2011年获得西北工业大学博士学位. 主要研究方向为信息融合, 计算机视觉和智能建造. E-mail: zongfangma@xauat.edu.cn

苏晓杰：重庆大学自动化学院教授. 2013年获得哈尔滨工业大学控制科学与工程专业博士学位. 主要研究方向为智能控制系统及其在无人系统中的应用. E-mail: suxiaojie@cqu.edu.cn

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出版历程
- 收稿日期: 2024-11-11
- 录用日期: 2025-03-05
- 网络出版日期: 2025-06-30

Generalized Memory Sliding Mode Control for Time-delay Markov Jump Systems Based on Event-triggered Observers

1.
College of Information and Control Engineering, Xi＇an University of Architecture and Technology, Xi＇an 710311
2.
College of Automation, Chongqing University, Chongqing 400044

Funds: Supported by National Natural Science Foundation of China (62306228, 62441237) and Shaanxi Province Key Research and Development Program (2024GX-YBXM-132)

More Information

Author Bio:
YANG Yue Associate professor at the College of Information and Control Engineering, Xi＇an University of Architecture and Technology. She received her Ph.D. degree in control theory and engineering from Chongqing University in 2022. Her main research interest is the security control of intelligent unmanned systems. Corresponding author of this paper

HUANG Jia-Nan Master student at the College of Information and Control Engineering, Xi＇an University of Architecture and Technology. His research interest covers sliding mode control, fuzzy control, and their applications in robotic systems

MA Zong-Fang Professor at the College of Information and Control Engineering, Xi＇an University of Architecture and Technology. He received his Ph.D. degree from Northwestern Polytechnical University in 2011. His research interest covers information fusion, computer vision, and intelligent construction

SU Xiao-Jie Professor at the College of Automation, Chongqing University. He received his Ph.D. degree in control science and engineering from the Harbin Institute of Technology in 2013. His research interest covers intelligent control systems and their applications in unmanned systems

摘要

摘要: 马尔科夫跳跃系统镇定过程常伴随通信信道堵塞、状态信息未知、时滞效应不全等问题. 基于此, 提出一种基于动态事件触发观测器的广义记忆异步滑模控制器. 其中动态事件触发观测器结合丢包补偿, 克服了已有文献单一考虑网络环境下频繁数据传输导致的通道堵塞问题. 针对观测时滞状态与控制器异步行为, 在滑模函数中引入时变时滞及其边界条件, 设计基于隐马尔科夫模型的广义记忆异步滑模控制器. 由于高效时滞利用率和多独立控制增益相互补偿, 闭环系统稳定性、收敛速度和超调等静态/动态性能较传统记忆/无记忆滑模控制器稳定提升. 同时, 为进一步耦合广义记忆控制时滞信息, 提出一组指数型反凸组合不等式, 通过预置指数型参数, 在不增加计算复杂度的前提下, 降低广义控制镇定条件保守性, 提升控制增益镇定精度. 最后通过数值算例和柔性机械臂实例验证了所提控制方案的有效性.
- 时滞马尔科夫跳跃系统 /
- 动态事件触发观测器 /
- 广义记忆异步滑模控制器 /
- 反凸不等式
Abstract: The stabilization of Markov jump systems is often accompanied by problems such as communication channel congestion, unknown state information, and incomplete time-delay effects. To address these challenges, this paper proposes a generalized memory asynchronous sliding mode controller based on a dynamic event-triggered observer. The observer incorporates packet loss compensation to overcome the single consideration of channel congestion caused by frequent data transmission in existing literatures under network environments. To tackle both the observed time-delay states and the asynchronous nature of the controller, the time-varying delay and its boundary conditions are integrated into the sliding mode function to design a generalized memory asynchronous sliding mode controller based on hidden Markov models. Owing to efficient delay utilization and mutual compensation of multiple independent control gains, the static/dynamic performances of the closed-loop system, such as stability, convergence speed, and overshoot, is significantly enhanced compared to traditional memory/memoryless sliding mode controllers. Furthermore, in order to better integrated the time-delay information into generalized memory control, a set of exponentially reciprocally convex combination inequalities are proposed. By presetting the exponential parameters, the conservativeness of the generalized control stabilization condition is reduced without increasing computational complexity, and the accuracy of the control gain stabilization is improved. Finally, the effectiveness of the proposed control scheme is verified through numerical example and flexible robotic arm example.
- Time-delay Markov jump system /
- dynamic event-triggered observer /
- generalized memory asynchronous sliding mode controller /
- reciprocally convex inequality

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图 1 异步行为观测

Fig. 1 Asynchronous behavior observation

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图 2 信号触发时刻与释放间隔

Fig. 2 Signal triggering time and release interval

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图 5 闭环系统状态轨迹

Fig. 5 Closed-loop system state trajectory

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图 3 闭环系统状态轨迹

Fig. 3 Closed-loop system state trajectory

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图 4 闭环系统状态轨迹

Fig. 4 Closed-loop system state trajectory

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图 6 应用场景((a)模式1; (b)模式2;(c)模式3; (d)模式4)

Fig. 6 Application scenarios ((a) Mode 1; (b) Mode 2;(c) Mode 3; (d) Mode 4)

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图 7 信号触发时刻与释放间隔

Fig. 7 Signal triggering time and release interval

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图 8 异步行为观测

Fig. 8 Asynchronous behavior observation

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图 9 闭环系统状态轨迹

Fig. 9 Closed-loop system state trajectory

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