Prosthetic devices designed to assist individuals with damaged or missing body parts have made significant strides,particularly with advancements in machine intelligence and bioengineering.Initially focused on movemen...Prosthetic devices designed to assist individuals with damaged or missing body parts have made significant strides,particularly with advancements in machine intelligence and bioengineering.Initially focused on movement assistance,the field has shifted towards developing prosthetics that function as seamless extensions of the human body.During this progress,a key challenge remains the reduction of interface artifacts between prosthetic components and biological tissues.Soft electronics offer a promising solution due to their structural flexibility and enhanced tissue adaptability.However,achieving full integration of prosthetics with the human body requires both artificial perception and efficient transmission of physical signals.In this context,synaptic devices have garnered attention as next-generation neuromorphic computing elements because of their low power consumption,ability to enable hardware-based learning,and high compatibility with sensing units.These devices have the potential to create artificial pathways for sensory recognition and motor responses,forming a“sensory-neuromorphic system”that emulates synaptic junctions in biological neurons,thereby connecting with impaired biological tissues.Here,we discuss recent developments in prosthetic components and neuromorphic applications with a focus on sensory perception and sensorimotor actuation.Initially,we explore a prosthetic system with advanced sensory units,mechanical softness,and artificial intelligence,followed by the hardware implementation of memory devices that combine calculation and learning functions.We then highlight the importance and mechanisms of soft-form synaptic devices that are compatible with sensing units.Furthermore,we review an artificial sensory-neuromorphic perception system that replicates various biological senses and facilitates sensorimotor loops from sensory receptors,the spinal cord,and motor neurons.Finally,we propose insights into the future of closed-loop neuroprosthetics through the technical integration of soft electronics,including bio-integrated sensors and synaptic devices,into prosthetic systems.展开更多
Numerical simulation plays an important role in the dynamic analysis of multibody system.With the rapid development of computer science,the numerical solution technology has been further developed.Recently,data-driven...Numerical simulation plays an important role in the dynamic analysis of multibody system.With the rapid development of computer science,the numerical solution technology has been further developed.Recently,data-driven method has become a very popular computing method.However,due to lack of necessary mechanism information of the traditional pure data-driven methods based on neural network,its numerical accuracy cannot be guaranteed for strong nonlinear system.Therefore,this work proposes a mechanism-data hybrid-driven strategy for solving nonlinear multibody system based on physics-informed neural network to overcome the limitation of traditional data-driven methods.The strategy proposed in this paper introduces scaling coefficients to introduce the dynamic model of multibody system into neural network,ensuring that the training results of neural network conform to the mechanics principle of the system,thereby ensuring the good reliability of the data-driven method.Finally,the stability,generalization ability and numerical accuracy of the proposed method are discussed and analyzed using three typical multibody systems,and the constrained default situations can be controlled within the range of 10^(-2)-10^(-4).展开更多
Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the p...Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the pushing force acting on the wellbore in different sizes and directions within a circular range,ultimately allowing the wellbore trajectory to be drilled in a predetermined direction.By analyzing its mathematical principles and the actual characteristics of the instrument,a vector force closed-loop control method,including steering and holding modes,was designed.The adjustment criteria for the three hydraulic modules are determined to achieve rapid adjustment of the vector force.The theoretical feasibility of the developed method was verified by comparing its results with the on-site application data of an imported rotary guidance system.展开更多
Conventional open-loop deep brain stimulation(DBS)systems with fixed parameters fail to accommodate interindividual pathological differences in Parkinson's disease(PD)management while potentially inducing adverse ...Conventional open-loop deep brain stimulation(DBS)systems with fixed parameters fail to accommodate interindividual pathological differences in Parkinson's disease(PD)management while potentially inducing adverse effects and causing excessive energy consumption.In this paper,we present an adaptive closed-loop framework integrating a Yogi-optimized proportional–integral–derivative neural network(Yogi-PIDNN)controller.The Yogi-augmented gradient adaptation mechanism accelerates the convergence of general PIDNN controllers in high-dimensional nonlinear control systems while reducing control energy usage.In addition,a system identification method establishes input–output dynamics for pre-training stimulation waveforms,bypassing real-time parameter-tuning constraints and thereby enhancing closed-loop adaptability.Finally,a theoretical analysis based on Lyapunov stability criteria establishes a sufficient condition for closed-loop stability within the identified model.Computational validations demonstrate that our approach restores thalamic relay reliability while reducing energy consumption by(81.0±0.7)%across multi-frequency tests.This study advances adaptive neuromodulation by synergizing data-driven pre-training with stability-guaranteed real-time control,offering a novel framework for energy-efficient and personalized Parkinson's therapy.展开更多
The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with ...The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.展开更多
This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working...This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working environments and safety requirements.The nonlinear feedback method is used to improve the closed-loop gain shaping algorithm.By introducing the sine function,the problem of excessive control energy of the system can be effectively solved.Moreover,an integral separation design is used to solve the influence of the integral term in conventional PID controllers on the transient performance of the system.In this paper,a common 32.98 m large fiberglass reinforced plastic(FRP)trawler is adopted for simulation research at the winds scale of Beaufort No.7.The results show that the track error is smaller than 3.5 m.The method is safe,feasible,concise and effective and has popularization value in the direction of fishing ship trajectory tracking control.This method can be used to improve the level of informatization and intelligence of fishing ships.展开更多
Based on the theory of multibody system dynamics, the spatial kinematics analysis of the Mcpherson independent suspension widely used in the car was carried out. A practical and simpler method was provided to reduce t...Based on the theory of multibody system dynamics, the spatial kinematics analysis of the Mcpherson independent suspension widely used in the car was carried out. A practical and simpler method was provided to reduce the number of the generalized coordinates and constraint functions. By solving the nonlinear equations, the motion of any points in the whole suspension and wheel system can be predicted, including the spatial changes of the wheel alignment parameters which are of great importance to the car performances.展开更多
The theory of multibody system dynamics is used to simulate valve trains' kinematics and dynamics characteristics, and the methods of establishing and analyzing the multibody system dynamics model for valve trains...The theory of multibody system dynamics is used to simulate valve trains' kinematics and dynamics characteristics, and the methods of establishing and analyzing the multibody system dynamics model for valve trains are discussed. Since most of the flexible bodies of a valve train are slender parts, the finite segment method is used to build their models. Other parts such as cams, valve heads etc., are built as rigid bodies. After applying the constraints, forces and motions, the establishing of the whole system is accomplished, and the Lagrange's multiplier method can be used to obtain its dynamics constitutive equations. As an example, a valve trains multibody system model of 4100QB engine made by the Yunnan Internal Combustion Engine Limited Liability Company is established, and the analysis results obtained show that its working performance is generally good except that the air pass ability and the lubrication effect of the cam and the tappet have to be improved.展开更多
A novel closed-loop control strategy of a silicon microgyroscope （SMG） is proposed. The SMG is sealed in metal can package in drive and sense modes and works under the air pressure of 10 Pa. Its quality factor reach...A novel closed-loop control strategy of a silicon microgyroscope （SMG） is proposed. The SMG is sealed in metal can package in drive and sense modes and works under the air pressure of 10 Pa. Its quality factor reaches greater than l0 000. Self-oscillating and closed-loop methods based on electrostatic force feedback are adopted in both measure and control circuits. Both single side driving and sensing methods are used to simplify the drive circuit. These dual channel decomposition and reconstruction closed loops are applied in sense modes. The testing results demonstrate that useful signals and guadrature signals do not interact with each other because of the decoupling of their phases. Under the condition of a scale factor of 9. 6 mV/（（°） .s）, in a full measurement range of±300 （°）/s, the zero bias stability reaches 28 （°）/h with a nonlinear coefficient of 400 × 10^-6 and a simulated bandwidth of more than 100 Hz. The overall performance is improved by two orders of magnitude in comparison to that at atmospheric pressure.展开更多
Wearable ultrasound devices represent a transformative advancement in therapeutic applications,offering noninvasive,continuous,and targeted treatment for deep tissues.These systems leverage flexible materials(e.g.,pie...Wearable ultrasound devices represent a transformative advancement in therapeutic applications,offering noninvasive,continuous,and targeted treatment for deep tissues.These systems leverage flexible materials(e.g.,piezoelectric composites,biodegradable polymers)and conformable designs to enable stable integration with dynamic anatomical surfaces.Key innovations include ultrasound-enhanced drug delivery through cavitation-mediated transdermal penetration,accelerated tissue regeneration via mechanical and electrical stimulation,and precise neuromodulation using focused acoustic waves.Recent developments demonstrate wireless operation,real-time monitoring,and closed-loop therapy,facilitated by energy-efficient transducers and AI-driven adaptive control.Despite progress,challenges persist in material durability,clinical validation,and scalable manufacturing.Future directions highlight the integration of nanomaterials,3D-printed architectures,and multimodal sensing for personalized medicine.This technology holds significant potential to redefine chronic disease management,postoperative recovery,and neurorehabilitation,bridging the gap between clinical and home-based care.展开更多
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korean government(MSIT)(No.2020R1C1C1005567)supported by the NAVER Digital Bio Innovation Research Fund,funded by NAVER Corporation(Grant No.[37-2023-0040])+3 种基金supported by Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2020-0-00261,Development of low power/low delay/self-power suppliable RF simultaneous information and power transfer system and stretchable electronic epineurium for wireless nerve bypass implementation)supported by Institute for Basic Science(IBS-R015-D1,IBSR015-D2)supported by a grant of the Korea-US Collaborative Research Fund(KUCRF)funded by the Ministry of Science and ICT and Ministry of Health&Welfare,Republic of Korea(Grant Number.RS-2024-00467213)。
文摘Prosthetic devices designed to assist individuals with damaged or missing body parts have made significant strides,particularly with advancements in machine intelligence and bioengineering.Initially focused on movement assistance,the field has shifted towards developing prosthetics that function as seamless extensions of the human body.During this progress,a key challenge remains the reduction of interface artifacts between prosthetic components and biological tissues.Soft electronics offer a promising solution due to their structural flexibility and enhanced tissue adaptability.However,achieving full integration of prosthetics with the human body requires both artificial perception and efficient transmission of physical signals.In this context,synaptic devices have garnered attention as next-generation neuromorphic computing elements because of their low power consumption,ability to enable hardware-based learning,and high compatibility with sensing units.These devices have the potential to create artificial pathways for sensory recognition and motor responses,forming a“sensory-neuromorphic system”that emulates synaptic junctions in biological neurons,thereby connecting with impaired biological tissues.Here,we discuss recent developments in prosthetic components and neuromorphic applications with a focus on sensory perception and sensorimotor actuation.Initially,we explore a prosthetic system with advanced sensory units,mechanical softness,and artificial intelligence,followed by the hardware implementation of memory devices that combine calculation and learning functions.We then highlight the importance and mechanisms of soft-form synaptic devices that are compatible with sensing units.Furthermore,we review an artificial sensory-neuromorphic perception system that replicates various biological senses and facilitates sensorimotor loops from sensory receptors,the spinal cord,and motor neurons.Finally,we propose insights into the future of closed-loop neuroprosthetics through the technical integration of soft electronics,including bio-integrated sensors and synaptic devices,into prosthetic systems.
基金supported by the National Natural Science Foundation of China(Grant No.U2241263)the fellowship of China Postdoctoral Science Foundation(Grant No.2024M750310).
文摘Numerical simulation plays an important role in the dynamic analysis of multibody system.With the rapid development of computer science,the numerical solution technology has been further developed.Recently,data-driven method has become a very popular computing method.However,due to lack of necessary mechanism information of the traditional pure data-driven methods based on neural network,its numerical accuracy cannot be guaranteed for strong nonlinear system.Therefore,this work proposes a mechanism-data hybrid-driven strategy for solving nonlinear multibody system based on physics-informed neural network to overcome the limitation of traditional data-driven methods.The strategy proposed in this paper introduces scaling coefficients to introduce the dynamic model of multibody system into neural network,ensuring that the training results of neural network conform to the mechanics principle of the system,thereby ensuring the good reliability of the data-driven method.Finally,the stability,generalization ability and numerical accuracy of the proposed method are discussed and analyzed using three typical multibody systems,and the constrained default situations can be controlled within the range of 10^(-2)-10^(-4).
基金supported by the Opening Foundation of China National Logging Corporation(CNLC20229C06)the China Petroleum Technical Service Corporation's science project'Development and application of 475 rotary steering system'(2024T-001001)。
文摘Rotary steering systems(RSSs)have been increasingly used to develop horizontal wells.A static push-the-bit RSS uses three hydraulic modules with varying degrees of expansion and contraction to achieve changes in the pushing force acting on the wellbore in different sizes and directions within a circular range,ultimately allowing the wellbore trajectory to be drilled in a predetermined direction.By analyzing its mathematical principles and the actual characteristics of the instrument,a vector force closed-loop control method,including steering and holding modes,was designed.The adjustment criteria for the three hydraulic modules are determined to achieve rapid adjustment of the vector force.The theoretical feasibility of the developed method was verified by comparing its results with the on-site application data of an imported rotary guidance system.
基金supported by the National Natural Science Foundation of China(Grant Nos.12372064 and 12172291)the Youth and Middle-Aged Science and Technology Development Program of Shanghai Institute of Technology(Grant No.ZQ2024-10)。
文摘Conventional open-loop deep brain stimulation(DBS)systems with fixed parameters fail to accommodate interindividual pathological differences in Parkinson's disease(PD)management while potentially inducing adverse effects and causing excessive energy consumption.In this paper,we present an adaptive closed-loop framework integrating a Yogi-optimized proportional–integral–derivative neural network(Yogi-PIDNN)controller.The Yogi-augmented gradient adaptation mechanism accelerates the convergence of general PIDNN controllers in high-dimensional nonlinear control systems while reducing control energy usage.In addition,a system identification method establishes input–output dynamics for pre-training stimulation waveforms,bypassing real-time parameter-tuning constraints and thereby enhancing closed-loop adaptability.Finally,a theoretical analysis based on Lyapunov stability criteria establishes a sufficient condition for closed-loop stability within the identified model.Computational validations demonstrate that our approach restores thalamic relay reliability while reducing energy consumption by(81.0±0.7)%across multi-frequency tests.This study advances adaptive neuromodulation by synergizing data-driven pre-training with stability-guaranteed real-time control,offering a novel framework for energy-efficient and personalized Parkinson's therapy.
基金supported by the National Natural Science Foundation of China(Grant Nos.12272123 and 12302047)the Natural Science Foundation of Jiangsu Province(Grant No.BK20231185)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.SJCX24_0192).
文摘The state estimation of the flexible multibody systems is a vital issue since it is the base of effective control and condition monitoring.The research on the state estimation method of flexible multibody system with large deformation and large rotation remains rare.In this investigation,a state estimator based on multiple nonlinear Kalman filtering algorithms was designed for the flexible multibody systems containing large flexibility components that were discretized by absolute nodal coordinate formulation(ANCF).The state variable vector was constructed based on the independent coordinates which are identified through the constraint Jacobian.Three types of Kalman filters were used to compare their performance in the state estimation for ANCF.Three cases including flexible planar rotating beam,flexible four-bar mechanism,and flexible rotating shaft were employed to verify the proposed state estimator.According to the different performances of the three types of Kalman filter,suggestions were given for the construction of the state estimator for the flexible multibody system.
基金supported by Liaoning Provincial Department of Education 2023 Basic Research Projects for Universities and Colleges(Grant No.JYTQN2023131)Liaoning Provincial Science and Technology Program:Cooperative Control and Recognition of Unmanned Vessels for Fishing Vessel Operation Scenarios(Grant No.600024003)Liaoning Provincial Department of Education Scientific Research Funding Project(Grant No.LJKZ0726).
文摘This paper proposes a separated trajectory tracking controller for fishing ships at sea state level 6 to solve the trajectory tracking problem of a fishing ship in a 6-level sea state,and to adapt to different working environments and safety requirements.The nonlinear feedback method is used to improve the closed-loop gain shaping algorithm.By introducing the sine function,the problem of excessive control energy of the system can be effectively solved.Moreover,an integral separation design is used to solve the influence of the integral term in conventional PID controllers on the transient performance of the system.In this paper,a common 32.98 m large fiberglass reinforced plastic(FRP)trawler is adopted for simulation research at the winds scale of Beaufort No.7.The results show that the track error is smaller than 3.5 m.The method is safe,feasible,concise and effective and has popularization value in the direction of fishing ship trajectory tracking control.This method can be used to improve the level of informatization and intelligence of fishing ships.
文摘Based on the theory of multibody system dynamics, the spatial kinematics analysis of the Mcpherson independent suspension widely used in the car was carried out. A practical and simpler method was provided to reduce the number of the generalized coordinates and constraint functions. By solving the nonlinear equations, the motion of any points in the whole suspension and wheel system can be predicted, including the spatial changes of the wheel alignment parameters which are of great importance to the car performances.
文摘The theory of multibody system dynamics is used to simulate valve trains' kinematics and dynamics characteristics, and the methods of establishing and analyzing the multibody system dynamics model for valve trains are discussed. Since most of the flexible bodies of a valve train are slender parts, the finite segment method is used to build their models. Other parts such as cams, valve heads etc., are built as rigid bodies. After applying the constraints, forces and motions, the establishing of the whole system is accomplished, and the Lagrange's multiplier method can be used to obtain its dynamics constitutive equations. As an example, a valve trains multibody system model of 4100QB engine made by the Yunnan Internal Combustion Engine Limited Liability Company is established, and the analysis results obtained show that its working performance is generally good except that the air pass ability and the lubrication effect of the cam and the tappet have to be improved.
基金The National High Technology Research and Development Program of China (863Program)(No.2002AA812038)the National Defense Pre-Research Support Program (No.41308050109)
文摘A novel closed-loop control strategy of a silicon microgyroscope （SMG） is proposed. The SMG is sealed in metal can package in drive and sense modes and works under the air pressure of 10 Pa. Its quality factor reaches greater than l0 000. Self-oscillating and closed-loop methods based on electrostatic force feedback are adopted in both measure and control circuits. Both single side driving and sensing methods are used to simplify the drive circuit. These dual channel decomposition and reconstruction closed loops are applied in sense modes. The testing results demonstrate that useful signals and guadrature signals do not interact with each other because of the decoupling of their phases. Under the condition of a scale factor of 9. 6 mV/（（°） .s）, in a full measurement range of±300 （°）/s, the zero bias stability reaches 28 （°）/h with a nonlinear coefficient of 400 × 10^-6 and a simulated bandwidth of more than 100 Hz. The overall performance is improved by two orders of magnitude in comparison to that at atmospheric pressure.
基金the support from the start-up of the University of Missouri-Columbia。
文摘Wearable ultrasound devices represent a transformative advancement in therapeutic applications,offering noninvasive,continuous,and targeted treatment for deep tissues.These systems leverage flexible materials(e.g.,piezoelectric composites,biodegradable polymers)and conformable designs to enable stable integration with dynamic anatomical surfaces.Key innovations include ultrasound-enhanced drug delivery through cavitation-mediated transdermal penetration,accelerated tissue regeneration via mechanical and electrical stimulation,and precise neuromodulation using focused acoustic waves.Recent developments demonstrate wireless operation,real-time monitoring,and closed-loop therapy,facilitated by energy-efficient transducers and AI-driven adaptive control.Despite progress,challenges persist in material durability,clinical validation,and scalable manufacturing.Future directions highlight the integration of nanomaterials,3D-printed architectures,and multimodal sensing for personalized medicine.This technology holds significant potential to redefine chronic disease management,postoperative recovery,and neurorehabilitation,bridging the gap between clinical and home-based care.
