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A Bio-Inspired Integration Model of Basal Ganglia and Cerebellum for Motion Learning of a Musculoskeletal Robot

Journal of Systems Science & Complexity 2024年第1期37卷 82-113页

作者： ZHANG Jinhan CHEN Jiahao ZHONG Shanlin QIAO Hong state key laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China.

It is a significant research direction for highly complex musculoskeletal robots that how to develop the ability of motion learning and generalization.The cooperations of multiple brain regions are crucial to improving motion performance.Inspired by the neural mechanisms of structures,functions,and interconnections of basal ganglia and cerebellum,a biologically inspired integration model for motor learning of musculoskeletal robots is proposed.Based on the neural characteristics of the basal ganglia,the basal ganglia actor network,which mainly simulates the dorsal striatum,outputs motion commands,and the basal ganglia critic network,which simulates the ventral striatum,estimates actionstate values.Their network parameters are updated using the soft actor-critic method.Based on the sensorimotor prediction mechanism of the cerebellum,the cerebellum network evaluates the state feature extraction quality of the basal ganglia actor network and then updates the weights of its feature layer.This learning method is proven to converge to the optimal policy.Furthermore,drawing on the mechanism of dopaminergic dynamic regulation in the basal ganglia,the adaptive adjustment of target entropy and the dopaminergic experience replay are proposed to further improve the integration model,which contributes to the exploration-exploitation trade-off of motor learning.The bio-inspired integration model is validated on a musculoskeletal system.Experimental results indicate that this model can effectively control the musculoskeletal robot to accomplish the motion task from random starting locations to random target positions with high precision and robustness.

关键词： Basal ganglia and cerebellum bio-inspired integration model motion learning musculoskeletal robot reinforcement learning.

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Microstructure evolution and strengthening mechanism of high -performance powder metallurgy TA15 titanium alloy by hot rolling

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International Journal of Minerals,Metallurgy and Materials 2024年第6期31卷 1426-1436页

作者： Ying Gao Ce Zhang Jiazhen Zhang Xin Lu Beijing Advanced Innovation Center for Materials Genome Engineering State Key Laboratory for Advanced Metals and MaterialsInstitute for Advanced Ma-terials and TechnologyUniversity of Science and Technology BeijingBeijing 100083China National Engineering Research Center for Advanced rolling Technology National Engineering Research Center for Flat Rolling EquipmentInstitute of Engin-eering TechnologyUniversity of Science and Technology BeijingBeijing 100083China

Hot deformation of sintered billets by powder metallurgy(PM)is an effective preparation technique for titanium alloys,which is more significant for high-alloying alloys.In this study,Ti–6.5Al–2Zr–Mo–V(TA15)titanium alloy plates were prepared by cold press-ing sintering combined with high-temperature hot rolling.The microstructure and mechanical properties under different process paramet-ers were investigated.Optical microscope,electron backscatter diffraction,and others were applied to characterize the microstructure evolution and mechanical properties strengthening mechanism.The results showed that the chemical compositions were uniformly dif-fused without segregation during sintering,and the closing of the matrix craters was accelerated by increasing the sintering temperature.The block was hot rolled at 1200℃ with an 80%reduction under only two passes without annealing.The strength and elongation of the plate at 20–25℃ after solution and aging were 1247 MPa and 14.0%,respectively,which were increased by 24.5%and 40.0%,respect-ively,compared with the as-sintered alloy at 1300℃.The microstructure was significantly refined by continuous dynamic recrystalliza-tion,which was completed by the rotation and dislocation absorption of the substructure surrounded by low-angle grain boundaries.After hot rolling combined with heat treatment,the strength and plasticity of PM-TA15 were significantly improved,which resulted from the dense,uniform,and fine recrystallization structure and the synergistic effect of multiple slip systems.

关键词： elemental powder powder metallurgy titanium alloy hot rolling strength and plasticity

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Study on Microstructure and Mechanical Properties of Hot Rolled Low Silicon Containing Phosphorus TRIP Steel

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稀有金属材料与工程 2011年第S3期40卷 228-233页

作者： Hou Xiaoying, Xu Yunbo, Wu Di state key laboratory of rolling and automation, Northeastern University, Shenyang 110819, China Northeastern Univ State Key Lab Rolling & Automat Shenyang 10819 Peoples R China

The effects of final air cooling temperature on the microstructure and mechanical properties of hot rolled 0.2C-1.9Mn-0.5Si-0.08P TRIP steel were studied by utilizing OM, SEM, TEM and tensile tests. Experimental results showed that in the multiphase microstructure of the investigated steel when the finish rolling temperature was about 820 ℃ and the final air cooling temperature was in the range of 630-700 ℃, the grain size of most of ferrite was finer (about 4 μm) and which had higher dislocation density, the bainite packets had chaotic orientations and lath boundaries of bainite were not quite straight, the retained austenite distributed in the ferrite grain boundaries or triradius was fine and dispersive, and their grain size was about 0.4-1.9 μm. With increasing the amount of ferrite, the volume fraction of retained austenite had a slight decrease. When the final air cooling temperature was 630 ℃, the steel had excellent mechanical properties, which was characterized by combination of continuous yielding, high strength (about 796 MPa) and high elongation (22.7%) as well as low yield/strength ratio (0.58); when the final air cooling temperature increased to 700 ℃, the matrix structure was bainite packets and the comprehensive properties were deteriorated.

关键词： hot rolled TRIP steel low silicon containing phosphorus microstructure and mechanical properties final air cooling temperature

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Prediction and Output Estimation of Pattern Moving in Non-Newtonian Mechanical Systems Based on Probability Density Evolution

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 515-536页

作者： Cheng Han Zhengguang Xu School of automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China key laboratory of Knowledge automation for Industrial Processes University of Science and Technology BeijingBeijing100083China

A prediction framework based on the evolution of pattern motion probability density is proposed for the output prediction and estimation problem of non-Newtonian mechanical systems,assuming that the system satisfies the generalized Lipschitz condition.As a complex nonlinear system primarily governed by statistical laws rather than Newtonian mechanics,the output of non-Newtonian mechanics systems is difficult to describe through deterministic variables such as state variables,which poses difficulties in predicting and estimating the system’s output.In this article,the temporal variation of the system is described by constructing pattern category variables,which are non-deterministic variables.Since pattern category variables have statistical attributes but not operational attributes,operational attributes are assigned to them by posterior probability density,and a method for analyzing their motion laws using probability density evolution is proposed.Furthermore,a data-driven form of pattern motion probabilistic density evolution prediction method is designed by combining pseudo partial derivative(PPD),achieving prediction of the probability density satisfying the system’s output uncertainty.Based on this,the final prediction estimation of the system’s output value is realized by minimum variance unbiased estimation.Finally,a corresponding PPD estimation algorithm is designed using an extended state observer(ESO)to estimate the parameters to be estimated in the proposed prediction method.The effectiveness of the parameter estimation algorithm and prediction method is demonstrated through theoretical analysis,and the accuracy of the algorithm is verified by two numerical simulation examples.

关键词： Non-newtonian mechanical systems prediction and estimation pattern moving probability density evolution pseudo partial derivative

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Designing Proportional-Integral Consensus Protocols for Second-Order Multi-Agent Systems Using Delayed and Memorized state Information

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 878-892页

作者： Honghai Wang Qing-Long Han the College of Information Science and Engineering State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern UniversityShenyang 110819China the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

This paper is concerned with consensus of a secondorder linear time-invariant multi-agent system in the situation that there exists a communication delay among the agents in the network.A proportional-integral consensus protocol is designed by using delayed and memorized state information.Under the proportional-integral consensus protocol,the consensus problem of the multi-agent system is transformed into the problem of asymptotic stability of the corresponding linear time-invariant time-delay system.Note that the location of the eigenvalues of the corresponding characteristic function of the linear time-invariant time-delay system not only determines the stability of the system,but also plays a critical role in the dynamic performance of the system.In this paper,based on recent results on the distribution of roots of quasi-polynomials,several necessary conditions for Hurwitz stability for a class of quasi-polynomials are first derived.Then allowable regions of consensus protocol parameters are estimated.Some necessary and sufficient conditions for determining effective protocol parameters are provided.The designed protocol can achieve consensus and improve the dynamic performance of the second-order multi-agent system.Moreover,the effects of delays on consensus of systems of harmonic oscillators/double integrators under proportional-integral consensus protocols are investigated.Furthermore,some results on proportional-integral consensus are derived for a class of high-order linear time-invariant multi-agent systems.

关键词： Consensus protocol Hurwitz stability multi-agent systems quasi-polynomials time delay

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Intuitive Human-Robot-Environment Interaction With EMG Signals:A Review

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1075-1091页

作者： Dezhen Xiong Daohui Zhang Yaqi Chu Yiwen Zhao Xingang Zhao state key laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016 Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169 University of Chinese Academy of Sciences Beijing 100049China

A long history has passed since electromyography(EMG)signals have been explored in human-centered robots for intuitive interaction.However,it still has a gap between scientific research and real-life applications.Previous studies mainly focused on EMG decoding algorithms,leaving a dynamic relationship between the human,robot,and uncertain environment in real-life scenarios seldomly concerned.To fill this gap,this paper presents a comprehensive review of EMG-based techniques in human-robot-environment interaction(HREI)systems.The general processing framework is summarized,and three interaction paradigms,including direct control,sensory feedback,and partial autonomous control,are introduced.EMG-based intention decoding is treated as a module of the proposed paradigms.Five key issues involving precision,stability,user attention,compliance,and environmental awareness in this field are discussed.Several important directions,including EMG decomposition,robust algorithms,HREI dataset,proprioception feedback,reinforcement learning,and embodied intelligence,are proposed to pave the way for future research.To the best of what we know,this is the first time that a review of EMG-based methods in the HREI system is summarized.It provides a novel and broader perspective to improve the practicability of current myoelectric interaction systems,in which factors in human-robot interaction,robot-environment interaction,and state perception by human sensations are considered,which has never been done by previous studies.

关键词： robot summarized Robot

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Attention Markets of Blockchain-Based Decentralized Autonomous Organizations

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1370-1380页

作者： Juanjuan Li Rui Qin Sangtian Guan Wenwen Ding Fei Lin Fei-Yue Wang state key laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China state key laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

The attention is a scarce resource in decentralized autonomous organizations(DAOs),as their self-governance relies heavily on the attention-intensive decision-making process of“proposal and voting”.To prevent the negative effects of pro-posers’attention-capturing strategies that contribute to the“tragedy of the commons”and ensure an efficient distribution of attention among multiple proposals,it is necessary to establish a market-driven allocation scheme for DAOs’attention.First,the Harberger tax-based attention markets are designed to facilitate its allocation via continuous and automated trading,where the individualized Harberger tax rate(HTR)determined by the pro-posers’reputation is adopted.Then,the Stackelberg game model is formulated in these markets,casting attention to owners in the role of leaders and other competitive proposers as followers.Its equilibrium trading strategies are also discussed to unravel the intricate dynamics of attention pricing.Moreover,utilizing the single-round Stackelberg game as an illustrative example,the existence of Nash equilibrium trading strategies is demonstrated.Finally,the impact of individualized HTR on trading strategies is investigated,and results suggest that it has a negative correlation with leaders’self-accessed prices and ownership duration,but its effect on their revenues varies under different conditions.This study is expected to provide valuable insights into leveraging attention resources to improve DAOs’governance and decision-making process.

关键词： Attention decentralized autonomous organizations Harberger tax Stackelberg game.

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Deep Reinforcement Learning or Lyapunov Analysis?A Preliminary Comparative Study on Event-Triggered Optimal Control

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1702-1704页

作者： Jingwei Lu Lefei Li Qinglai Wei Fei-Yue Wang IEEE the Department of Industrial Engineering Tsinghua UniversityBeijing 100084China The state key laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter develops a novel method to implement event-triggered optimal control(ETOC) for discrete-time nonlinear systems using parallel control and deep reinforcement learning(DRL), referred to as Deep-ETOC. The developed Deep-ETOC method introduces the communication cost into the performance index through parallel control, so that the developed method enables control systems to learn ETOC policies directly without triggering conditions.

关键词： Deep letter enable

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Progress in research on metal-based materials in stabilized Zn anodes

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Rare Metals 2024年第1期43卷 20-40页

作者： Le Li Shao-Feng Jia Ming-Hui Cao Yong-Qiang Ji Heng-Wei Qiu Dan Zhang Shaanxi key laboratory of Industrial automation School of Mechanical EngineeringShaanxi University of TechnologyHanzhong 723001China School of Electronic and Information Engineering Qingdao UniversityQingdao 266071China state key laboratory for Artifcial Microstructure and Mesoscopic Physics School of PhysicsPeking UniversityBeijing 100871China Department of Chemistry Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical BiologyTsinghua UniversityBeijing 100084China Shaanxi key laboratory of Catalysis School of Chemistry and Environment ScienceShaanxi University of TechnologyHanzhong 723001China

Aqueous zinc-ion batteries(ZIBs) combine the benefits of metallic Zn anodes with those of aqueous electrolytes and are well suited for large-scale energy storage because of their inherent high safety, cost-effectiveness, and eco-friendliness. Currently, the practical application of such batteries is hindered by the poor cycling performance of Zn anodes due to uncontrolled dendrite formation and severe side reactions, although recent reports suggest that these problems can be mitigated through the modification of Zn anodes with metal-based materials.Given that the mechanisms of improving Zn deposition and the structural evolution of metal-based materials have not been systematically reviewed, we herein systematically overview the metal-based materials used to stabilize Zn anodes, starting with a brief summary of the anode working mechanism and the challenges faced by stabilized Zn anodes. Subsequently, the design principles of Zn anodes stabilized by metal-based materials and the related recent progress are reviewed, and the key challenges and perspectives for the future development of such Zn anodes are proposed.

关键词： Zinc-ion batteries(ZIBs) Zn anode Metalbased materials Alloying metal Stabilized Zn anodes

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UAV swarm air combat maneuver decision-making method based on multi-agent reinforcement learning and transferring

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Science China(Information Sciences) 2024年第8期67卷 49-66页

作者： Zhiqiang ZHENG Chen WEI Haibin DUAN state key laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beihang University

During short-range air combat involving unmanned aircraft vehicle(UAV) swarms, UAVs must make accurate maneuver decisions based on information from both enemy and friendly UAVs. This dual requirement of competition and cooperation presents a significant challenge in the field of unmanned air combat. In this paper, a method based on multi-agent reinforcement learning(MARL) is proposed to address this issue. An actor network containing three subnetworks that can handle different types of situational information is designed. Hence, the results from simpler one-on-one scenarios are leveraged to enhance the complex swarm air combat training process. Separate state spaces for local and global information are designed for the actor and critic networks. A detailed reward function is proposed to encourage participation.To prevent lazy participants in air combat, a reward assignment operation is applied to distribute these dense rewards. Simulation testing and ablation experiments demonstrate that both the transfer operation and reward assignment operation can effectively deal with the swarm air combat scenario, and reflect the effectiveness of the proposed method.

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