Event-Triggered Sliding-Mode Control for a Discrete-Time Muscle-Driven Musculoskeletal System

doi:10.1109/TASE.2023.3319503

CORC > 自动化研究所 > 中国科学院自动化研究所 > 多模态人工智能系统全国重点实验室

	Event-Triggered Sliding-Mode Control for a Discrete-Time Muscle-Driven Musculoskeletal System
	Fan, Yerui 4,5; Wu, Yaxiong 4,5; Yuan, Jianbo 4,5; Gao, Jie 1,2,3,6; Qiao, Hong 1,2,3,6
刊名	IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
	2023-10-05
页码	15
关键词	Musculoskeletal system bio-inspired muscle model discrete-time system event-triggered control sliding mode controller
ISSN号	1545-5955
DOI	10.1109/TASE.2023.3319503
通讯作者	Qiao, Hong(hong.qiao@ia.ac.cn)
英文摘要	Bionic muscle-driven musculoskeletal systems can dynamically adjust the stiffness between active and antagonistic muscles to improve stability. However, they retain many problems, such as difficulty with sensory feedback control, which arises from the strong coupling of models and large computational loads encountered when optimizing the muscle force online. In this study, based on a bionic muscle model, an event-triggered-sliding-mode controller for a discrete-time-muscle-driven musculoskeletal system (MDMS) was designed to drive the system into a bounded region. Specifically, based on the Hamilton principle and discretization of muscle contraction dynamics, a new discrete-time-muscle-driven musculoskeletal model was constructed to facilitate the decoupling of the muscle model, feedback of the muscle state, and improvement of model control accuracy. Second, to guarantee the boundedness of the closed-loop system, an even-triggered-sliding-mode control law was established by introducing the input-to-state stable (ISS) method to a new type of discrete-time MDMS. The design ensured the convergence of different triggering cases, and an event-triggered-sliding-mode control law was established to obtain faster and smoother response characteristics. Finally, stability was ensured using the Lyapunov synthesis principle. The experimental results demonstrated that the proposed controller could effectively reduce the computational load while maintaining the same performance using a time-based approach. Note to Practitioners-The motivation of this study is to delve into the utilization of the Lyapunov control theory to enhance the control performance of the bionic muscle model. Additionally, it aimed to explore the initial application of the event-trigger mechanism within the musculoskeletal system. The primary focus is on discrete musculoskeletal system modeling, which facilitates the achievement of sensory feedback control for nonlinear muscle models characterized by strong coupling and a multi-segment structure. Using the proposed method, it is possible to regulate the muscle force based on sensory feedback using the principles of Lyapunov control theory. Furthermore, the application of event triggering mechanisms is explored with the goal of reducing the communicational load within musculoskeletal systems.
资助项目	Major Project of Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence
WOS研究方向	Automation & Control Systems
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:001165372600001
资助机构	Major Project of Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/55680]
专题	多模态人工智能系统全国重点实验室
通讯作者	Qiao, Hong
作者单位	1.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Beijing Key Lab Res & Applicat Robot Intelligence, Beijing 100190, Peoples R China 4.Beijing Key Lab Res & Applicat Robot Intelligence, Beijing 100190, Peoples R China 5.Univ Sci & Technol Beijing, Sch Mech Engn, Beijing 100083, Peoples R China 6.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Fan, Yerui,Wu, Yaxiong,Yuan, Jianbo,et al. Event-Triggered Sliding-Mode Control for a Discrete-Time Muscle-Driven Musculoskeletal System[J]. IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,2023:15.
APA	Fan, Yerui,Wu, Yaxiong,Yuan, Jianbo,Gao, Jie,&Qiao, Hong.(2023).Event-Triggered Sliding-Mode Control for a Discrete-Time Muscle-Driven Musculoskeletal System.IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING,15.
MLA	Fan, Yerui,et al."Event-Triggered Sliding-Mode Control for a Discrete-Time Muscle-Driven Musculoskeletal System".IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING (2023):15.