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Equilibrium-Point control and Robustness Analysis of Bioinspired Musculoskeletal Robotic system

IEEE-ASME TRANSACTIONS ON MECHATRONICS 2024年第3期29卷 1659-1669页

作者： Wu, Yaxiong Yuan, Jianbo Qiao, Hong Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China Beijing Key Lab Res & Applicat Robot Intelligence Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Shanghai 200031 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

Compared to general joint-link robotic systems, bioinspired musculoskeletal robotic systems provide more potential advantages in terms of robustness, flexibility, and operation accuracy. Research on bioinspired control and structure has been a hot topic in recent years, indicating that musculoskeletal robots are a promising option for next-generation robots. However, standard modeling and analysis of the system are scarce;therefore, controller design and stability proof are still open questions. Based on previous studies, we built the standardized state-space equations for musculoskeletal robotic dynamics. The robustness was proved through muscle contractile dynamics and the Lyapunov stability theorem. Furthermore, a bioinspired equilibrium-point (EP) controller was designed to realize high-precision target-reaching tasks that required low control frequency and computation cost. Simulations and experiments were conducted to demonstrate the conclusions of the theoretical analysis. The effectiveness and anti-interference abilities of the EP controller were initially verified. This study provides a promising direction for motion control in bioinspired musculoskeletal robotic systems. A relatively complete system model was established, and a preliminary controller design and proof framework was proposed, which offers a reference for research and applications of musculoskeletal robotic systems.

关键词： Bioinspired equilibrium-point control Lyapunov stability muscle model musculoskeletal robotics robustness

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Cardiovascular Outcomes in Patients with complex Type 2 Diabetes Mellitus Treated with the Dual SGLT Inhibitor Sotagliflozin: A Meta-analysis

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DIABETES THERAPY 2025年第3期16卷 485-498页

作者： Wang, Hong Zu, Quannan Lu, Ming Chen, Rongfa Tang, Zhangui Yang, Zhiren Peoples Hosp Guangxi Zhuang Autonomous Reg Dept Cardiol Nanning 530021 Guangxi Peoples R China Tianjin Univ Coll Management & Econ Tianjin 300072 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Huazhong Univ Sci & Technol Inst Cardiovasc Dis Tongji Med Coll Dept Endocrinol Wuhan 430032 Hubei Peoples R China

IntroductionScientific publications have shown sodium-glucose co-transporter-2 (SGLT2) inhibitors to have several beneficial effects in patients with complex type 2 diabetes mellitus (T2DM). However, sodium-glucose co-transporter-1 (SGLT-1) inhibitor is still under investigation in clinical trials. Recently, a dual inhibitor of sodium-glucose co-transporter (SGLT1/2), sotagliflozin, has been approved for use in patients with T2DM. In this analysis, we aimed to systematically compare the cardiovascular outcomes in patients with complex T2DM who were treated with the newly approved dual (SGLT 1 and 2) inhibitor *** databases, including Embase, MEDLINE, http://***, Web of Science, Google Scholar, the Cochrane database, and reference lists of relevant publications, were searched for publications comparing the novel SGLT1/2 inhibitor versus placebo for the treatment of patients with complex T2DM. The primary endpoint, including total number of deaths from cardiovascular causes, hospitalization for heart failure, and urgent visits for heart failure, death from cardiovascular causes, cardiac mortality, hospitalization for heart failure, non-fatal myocardial infarction, and total number of cardiac events, were considered as the endpoints in this analysis. The RevMan software version 5.4 was used to carry out the statistical analysis. Risk ratios (RR) with 95% confidence intervals (CI) were used to represent the data following *** total of 13,054 participants enrolled between 2017 and 2020 were included in this analysis, with 6734 participants assigned to sotagliflozin and 6320 assigned to placebo. The results of this analysis showed that the primary endpoint was significantly in favor of sotagliflozin with (RR: 0.73, 95% CI 0.67-0.80;P = 0.00001). Hospitalization for heart failure (RR: 0.67, 95% CI 0.60-0.75;P = 0.00001) and the total number of cardiac events (RR: 0.73, 95% CI 0.67-0.79;P = 0.00001) were also sign

关键词： Dual SGLT inhibitor Sotagliflozin Diabetes mellitus Heart failure Cardiovascular mortality Chronic kidney disease

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An Adaptive Time-Varying Impedance controller for Manipulators

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FRONTIERS IN NEUROROBOTICS 2022年 16卷 789842页

作者： Liang, Xu Su, Tingting Zhang, Zhonghai Zhang, Jie Liu, Shengda Zhao, Quanliang Yuan, Junjie Huang, Can Zhao, Lei He, Guangping North China Univ Technol Dept Mech & Elect Engn Beijing Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing Peoples R China Beijing Aerosp Measurement & Control Technol Co L Beijing Peoples R China

Aiming at the situation that the structural parameters of the general manipulators are uncertain, a time-varying impedance controller based on model reference adaptive control (MRAC) is proposed in this article. The proposed controller does not need to use acceleration-based feedback or to measure external loads and can tolerate considerable structure parameter errors. The global uniform asymptotic stability of the time-varying closed-loop system is analyzed, and a selection approach for control parameters is presented. It is demonstrated that, by using the proposed control parameter selection approach, the closed-loop system under the adaptive controller is equivalent to an existing result. The feasibility of the presented controller for the general manipulators is demonstrated by some numerical simulations.

关键词： adaptive intelligent control time-varying human-robot interaction MRAC

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Optimal Tracking control for a Discrete Time Nonlinear Nuclear Power system

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MATHEMATICAL PROBLEMS IN ENGINEERING 2022年第1期2022卷

作者： Luan, Zhenhua Wang, Mengxuan Zhang, Yuzhen Wei, Qinglai Zhou, Tianmin Guo, Zhiwu Ling, Jun China Nucl Power Engn Co Ltd State Key Lab Nucl Power Safety Monitoring Technol Shenzhen 518172 Guangdong Peoples R China Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Harbin Univ Sci & Technol Harbin Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Shenzhen Urban Publ Safety & Technol Inst Shenzhen 518046 Guangdong Peoples R China

Recently, increasing attention has been paid to nuclear power control with the appeals of clean energy and demands of power regulation to integrate into the power grid. However, a nuclear power system is a discrete-time (DT) nonlinear and complicated system, where the parameters entangle with intrinsic states. Furthermore, the need for huge computational ability due to the high-level order property in the nuclear reactor model causes many difficulties in the power control of nuclear industries. In this study, a new scheme of optimal tracking control for DT nonlinear nuclear power systems is provided to accomplish the power control of a 2500-MW pressurized water reactor (PWR) nuclear power plant. The proposed approach based on the value iteration method is a novel algorithm in the human intelligence community, which has a basic actor-critic structure with neural networks (NNs). The new approach has some modifications, where the cost function is redefined by leveraging the higher-order polynomial to substitute neural networks in the entire actor critic architecture. Simulation results of the 2500-MW PWR nuclear power plant are given to demonstrate the effectiveness of the developed method.

关键词： Power control

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Coordinated Adaptive Impedance control of Redundantly Actuated Parallel Manipulators

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IEEE TRANSACTIONS ON HUMAN-MACHINE systemS 2025年第3期55卷 323-332页

作者： Ma, Nan Cheneler, David He, Guangping Yuan, Junjie Bian, Gui-Bin Northwestern Polytech Univ Sch Mech & Elect Engn Xian 710072 Peoples R China Univ Lancaster Sch Engn Lancaster LA1 4YW England North China Univ Technol Dept Mech & Elect Engn Beijing 100144 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Redundantly actuated parallel mechanisms (RAPMs) have been widely adopted in advanced robotic systems and precision machine tools. It has been demonstrated that redundant actuation can improve the performance of mechatronic systems but introduce challenges with respect to control. One main difficulty is in establishing an accurate dynamic model of the RAPM system. With an inaccurate dynamic model, the torque applied by the actuators will be incorrect, leading to increased antagonistic forces in the system. To solve this problem, a novel coordinated adaptive impedance control approach based on a new adaptive impedance control law is presented here, along with proof of the stability of the closed-loop system. The control algorithm has been validated experimentally by a prototype cable-driven parallel manipulator. It can be seen from the experimental results that the proposed control method is an effective way to correct the antagonistic forces of the system, thus facilitating the improvement of its dynamic performance and its efficacy in different applications.

关键词： Impedance Robots Adaptation models Robot kinematics Actuators Stability analysis Kinematics Wires Steel Manipulator dynamics Actuation redundancy adaptive impedance control coordination control parallel manipulators uncertain model

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Bioinspired approach-sensitive neural network for collision detection in cluttered and dynamic backgrounds

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APPLIED SOFT COMPUTING 2022年 122卷

作者： Huang, Xiao Qiao, Hong Li, Hui Jiang, Zhihong Chinese Minist Educ Adv Innovat Ctr Intelligent Robots & Syst Sch Mechatron Engn Key Lab Biomimet Robots SystBeijing Inst Technol Beijing 100081 Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Rapid, accurate and robust detection of looming objects in cluttered moving backgrounds is a significant and challenging problem encountered when designing robotic visual systems to perform collision detection and avoidance tasks. Inspired by the neural circuit involved in the elementary motion vision of the mammalian retina, this study proposes a bioinspired approach-sensitive neural network (ASNN). The three main contributions of this work are as follows. First, a direction-selective visual processing module is built based on the spatiotemporal energy framework, which can estimate motion direction accurately via only two mutually perpendicular spatiotemporal filtering channels. Second, a novel approach-sensitive neural network is modeled as a push-pull structure formed by ON and OFF pathways, which responds strongly to approaching motion, but is insensitive to lateral motion. Finally, a method of direction-selective inhibition is introduced, which is able to effectively suppress translational backgrounds. Extensive synthetic and real robotic experiments indicate that the proposed model is able to not only detect collisions accurately and robustly in cluttered and dynamic backgrounds but also extract additional information on the approaching object, such as position and direction, which is critical for guiding rapid decision making. (C)& nbsp;2022 Published by Elsevier B.V.

关键词： Visual collision detection Bioinspiration Approach -sensitive neural network Spatiotemporal energy model

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Event-Triggered Sliding-Mode control for a Discrete-Time Muscle-Driven Musculoskeletal system

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年第4期21卷 5866-5880页

作者： Fan, Yerui Wu, Yaxiong Yuan, Jianbo Gao, Jie Qiao, Hong Univ Sci & Technol Beijing Sch Mech Engn Beijing 100083 Peoples R China Beijing Key Lab Res & Applicat Robot Intelligence Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Shanghai 200031 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Beijing Key Lab Res & Applicat Robot Intelligence Beijing 100190 Peoples R China

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 c

关键词： Musculoskeletal system bio-inspired muscle model discrete-time system event-triggered control sliding mode controller

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A Comparative Study of Machine Learning Models for Parkinson's Disease Detection

A Comparative Study of Machine Learning Models for Parkinson...

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International Conference on Decision Aid Sciences and Applications (DASA)

作者： Bunterngchit, Chayut Bunterngchit, Yuthachai Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Siam Univ Grad Sch Engn Bangkok Thailand

ISBN: (纸本)9781665495011

Parkinson's disease is a major public health concern, affecting over 6 million people worldwide. The objective of this paper is to assist doctors and clinicians in accurately detecting the disease at an early stage. Previous research proposed various models that gave very high accuracy. However, very few of them examined the processing time of each model, which is an important consideration in decision making. The most common method for diagnosing this disease is through voice signal recordings. This paper formulates 10 machine learning-based predictive models on a biomedical voice measurement dataset. A genetic algorithm is applied as a feature selection algorithm. The highest prediction accuracy after running 10 generations is 97.96%. The features of the most accurate model are reduced from 22 to 9 features. The processing time of the most accurate model is 1.83 seconds. The best improvement in accuracy after applying this feature selection algorithm is 16.33%.

关键词： Parkinson's disease genetic algorithm machine learning feature selection

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Containment control with input and velocity constraints

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AUTOMATICA 2022年 142卷

作者： Xu, Jiahao Lin, Peng Cheng, Long Dong, Hairong Cent South Univ Sch Automat Changsha 410083 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China

In this paper, containment control for double-integrator discrete-time multi-agent systems is investigated with switching graphs, nonconvex input constraints and nonconvex velocity constraints. In order to eliminate the nonlinearities caused by the nonconvex input and velocity constraints, we first introduce two time-varying scaling factors to transform the original constrained system into an unconstrained time-varying linear one. By proposing an inductive method based on the lower bounds of the scaling factors, we decouple the relevance of the two kinds of constraints and transform the obtained time-varying system into a new equivalent system. It is shown that all agents converge into the convex hull of the leaders even when switching graphs, nonconvex control input constraints and nonconvex velocity constraints coexist, as long as there exists at least one directed path from one of the leaders to each agent in the union of the communication graphs. Finally, a simulation example is given to illustrate the obtained theoretical results. (C) 2022 Elsevier Ltd. All rights reserved.

关键词： Multi-agent systems Containment control Nonconvex constraints Switching graphs

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4D mmWave Radar for Autonomous Driving Perception: A Comprehensive Survey

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第4期9卷 4606-4620页

作者： Fan, Lili Wang, Junhao Chang, Yuanmeng Li, Yuke Wang, Yutong Cao, Dongpu Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Jiangsu Ind Innovat Ctr Intelligent Equipment Co L Beijing 100081 Peoples R China Dalian Minzu Univ Sch Sci Dalian 116600 Peoples R China Waytous Co Ltd Beijing 100083 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Tsinghua Univ State Key Lab Intelligent Green Vehicle & Mobil Beijing 100084 Peoples R China

The rapid development of autonomous driving technology has driven continuous innovation in perception systems, with 4D millimeter-wave (mmWave) radar being one of the key sensing devices. Leveraging its all-weather operational characteristics and robust perception capabilities in challenging environments, 4D mmWave radar plays a crucial role in achieving highly automated driving. This review systematically summarizes the latest advancements and key applications of 4D mmWave radar in the field of autonomous driving. To begin with, we introduce the fundamental principles and technical features of 4D mmWave radar, delving into its comprehensive perception capabilities across distance, speed, angle, and time dimensions. Subsequently, we provide a detailed analysis of the performance advantages of 4D mmWave radar compared to other sensors in complex environments. We then discuss the latest developments in target detection and tracking using 4D mmWave radar, along with existing datasets in this domain. Finally, we explore the current technological challenges and future directions. This review offers researchers and engineers a comprehensive understanding of the cutting-edge technology and future development directions of 4D mmWave radar in the context of autonomous driving perception.

关键词： Radar Radar antennas Millimeter wave communication Microstrip antennas Antenna arrays Radar detection Autonomous vehicles 4D mmWave radar autonomous driving perception multi-modal fusion 3D object detection

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