In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be amel...In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ameliorated.Specially,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be addressed.To deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI control.The upper limb-robotic exoskeleton system is re-modelled as an artificial system.Depending on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical system.Furthermore,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and compared.Theoretical results substantiate the global convergence and robustness of the proposed controller in the presence of different external disturbances.In addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.展开更多
How to establish a self‐equilibrium configuration is vital for further kinematics and dynamics analyses of tensegrity mechanism.In this study,for investigating tensegrity form‐finding problems,a concise and efficien...How to establish a self‐equilibrium configuration is vital for further kinematics and dynamics analyses of tensegrity mechanism.In this study,for investigating tensegrity form‐finding problems,a concise and efficient dynamic relaxation‐noise tolerant zeroing neural network(DR‐NTZNN)form‐finding algorithm is established through analysing the physical properties of tensegrity structures.In addition,the non‐linear constrained opti-misation problem which transformed from the form‐finding problem is solved by a sequential quadratic programming algorithm.Moreover,the noise may produce in the form‐finding process that includes the round‐off errors which are brought by the approximate matrix and restart point calculating course,disturbance caused by external force and manufacturing error when constructing a tensegrity structure.Hence,for the purpose of suppressing the noise,a noise tolerant zeroing neural network is presented to solve the search direction,which can endow the anti‐noise capability to the form‐finding model and enhance the calculation capability.Besides,the dynamic relaxation method is contributed to seek the nodal coordinates rapidly when the search direction is acquired.The numerical results show the form‐finding model has a huge capability for high‐dimensional free form cable‐strut mechanisms with complicated topology.Eventually,comparing with other existing form‐finding methods,the contrast simulations reveal the excellent anti‐noise performance and calculation capacity of DR‐NTZNN form‐finding algorithm.展开更多
Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered t...Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered to be a powerful QPs solver due to its parallel processing capability and feasibility of hardware implementation[2].展开更多
To ensure the safety, comfort, and effectiveness of lower limb rehabilitation exoskeleton robots in the rehabilitation training process, compliance is a prerequisite for human–machine interaction safety. First, under...To ensure the safety, comfort, and effectiveness of lower limb rehabilitation exoskeleton robots in the rehabilitation training process, compliance is a prerequisite for human–machine interaction safety. First, under the premise of considering the mechanical structure of the lower limb rehabilitation exoskeleton robot (LLRER), when conducting the dynamic transmission of the exoskeleton knee joint, the soft axis is added to ensure that the rotation motion and torque are flexibly transmitted to any position to achieve flexible force transmission. Second, to realize the active compliance control of LLRER, the sliding mode impedance closed-loop controller is developed based on the kinematics and dynamics model of LLRER, and the stability of the designed control system is verified by Lyapunov method. Then the experiment is designed to track the collected bicycle rehabilitation motion data stably, and the algorithm and dynamic model are verified to satisfy the experimental requirements. Finally, aiming at the transmission efficiency and response performance of the soft shaft in the torque transmission process of the knee joint, the soft shaft transmission performance test is carried out to test the soft shaft transmission performance and realize the compliance of the LLRER, so as to ensure that the rehabilitation training can be carried out in a safe and comfortable interactive environment. Through the design of rehabilitation exercise training, it is verified that the LLRER of flexible transmission under sliding mode impedance control has good adaptability in the actual environment, and can achieve accurate and flexible control. During the experiment, the effectiveness of monitoring rehabilitation training is brought through the respiratory belt.展开更多
This paper introduces a rigid-flexible coupling wearable exoskeleton robot for lower limb,which is designed in light of gait biomechanics and beneficial for low limb movement disorders by implementing gait training.Th...This paper introduces a rigid-flexible coupling wearable exoskeleton robot for lower limb,which is designed in light of gait biomechanics and beneficial for low limb movement disorders by implementing gait training.The rationality of the proposed mechanism is shown with the implementation of the dynamic simulation through MSC ADAMS.For the purposes of lightweight,the exoskeleton mechanism is optimized through finite element analysis.It can be concluded from performance evaluation experiment,the mechanism has certain advantages over existing exoskeleton robots,namely,comfortable,lightweight,low cost,which can be utilized for rehabilitation training in medical institutions or as a daily-walking ancillary equipment for patients.展开更多
基金Key Science and Technology Projects of Jilin Province,China,Grant/Award Number:20230204081YYChangchun Science and Technology Project,Grant/Award Number:21ZY41National Natural Science Foundation of China,Grant/Award Numbers:61873304,62173048,62106023。
文摘In recent years,intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation,wherein the human-robot interaction(HRI)control strategy is a momentous part that needs to be ameliorated.Specially,the efficacy and robustness of the HRI control algorithm in the presence of unknown external disturbances deserve to be addressed.To deal with these urgent issues,in this study,artificial systems,computational experiments and a parallel execution intelligent control framework are constructed for the HRI control.The upper limb-robotic exoskeleton system is re-modelled as an artificial system.Depending on surface electromyogram-based subject's active motion intention in the practical system,a non-convex function activated anti-disturbance zeroing neurodynamic(NC-ADZND)controller is devised in the artificial system for parallel interaction and HRI control with the practical system.Furthermore,the linear activation function-based zeroing neurodynamic(LAF-ZND)controller and proportionalderivative(posterior deltoid(PD))controller are presented and compared.Theoretical results substantiate the global convergence and robustness of the proposed controller in the presence of different external disturbances.In addition,the simulation results verify that the NC-ADZND controller is better than the LAF-ZND and the PD controllers in respect of convergence order and anti-disturbance characteristics.
基金supported in part by the National Natural Science Foundation of China under grants 61873304,62173048,62106023in part by the China Postdoctoral Science Foundation Funded Project under grants 2018M641784 and 2019T120240+1 种基金also in part by the Key Science and Technology Projects of Jilin Province,China,under grant 20210201106GXalso in part by the Changchun Science and Technology Project under grant 21ZY41.
文摘How to establish a self‐equilibrium configuration is vital for further kinematics and dynamics analyses of tensegrity mechanism.In this study,for investigating tensegrity form‐finding problems,a concise and efficient dynamic relaxation‐noise tolerant zeroing neural network(DR‐NTZNN)form‐finding algorithm is established through analysing the physical properties of tensegrity structures.In addition,the non‐linear constrained opti-misation problem which transformed from the form‐finding problem is solved by a sequential quadratic programming algorithm.Moreover,the noise may produce in the form‐finding process that includes the round‐off errors which are brought by the approximate matrix and restart point calculating course,disturbance caused by external force and manufacturing error when constructing a tensegrity structure.Hence,for the purpose of suppressing the noise,a noise tolerant zeroing neural network is presented to solve the search direction,which can endow the anti‐noise capability to the form‐finding model and enhance the calculation capability.Besides,the dynamic relaxation method is contributed to seek the nodal coordinates rapidly when the search direction is acquired.The numerical results show the form‐finding model has a huge capability for high‐dimensional free form cable‐strut mechanisms with complicated topology.Eventually,comparing with other existing form‐finding methods,the contrast simulations reveal the excellent anti‐noise performance and calculation capacity of DR‐NTZNN form‐finding algorithm.
基金supported in part by the National Natural Science Foundation of China(61873304,62173048,62106023)the Key Science and Technology Projects of Jilin Province,China(20210201106GX)+2 种基金the Innovation and Entrepreneurship Talent funding Project of Jilin Province(2022QN04)the Changchun Science and Technology Project(21ZY41)Beijing Natural Science Foundation(2022MQ05)。
文摘Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered to be a powerful QPs solver due to its parallel processing capability and feasibility of hardware implementation[2].
基金supported in part by the National Natural Science Foundation of China under grants 61873304 and 62173048in part by the China Postdoctoral Science Foundation Funded Project under grant 2018M641784also in part by the Key Science and Technology Project of Jilin Province,China,grant nos.20200404208YY.
文摘To ensure the safety, comfort, and effectiveness of lower limb rehabilitation exoskeleton robots in the rehabilitation training process, compliance is a prerequisite for human–machine interaction safety. First, under the premise of considering the mechanical structure of the lower limb rehabilitation exoskeleton robot (LLRER), when conducting the dynamic transmission of the exoskeleton knee joint, the soft axis is added to ensure that the rotation motion and torque are flexibly transmitted to any position to achieve flexible force transmission. Second, to realize the active compliance control of LLRER, the sliding mode impedance closed-loop controller is developed based on the kinematics and dynamics model of LLRER, and the stability of the designed control system is verified by Lyapunov method. Then the experiment is designed to track the collected bicycle rehabilitation motion data stably, and the algorithm and dynamic model are verified to satisfy the experimental requirements. Finally, aiming at the transmission efficiency and response performance of the soft shaft in the torque transmission process of the knee joint, the soft shaft transmission performance test is carried out to test the soft shaft transmission performance and realize the compliance of the LLRER, so as to ensure that the rehabilitation training can be carried out in a safe and comfortable interactive environment. Through the design of rehabilitation exercise training, it is verified that the LLRER of flexible transmission under sliding mode impedance control has good adaptability in the actual environment, and can achieve accurate and flexible control. During the experiment, the effectiveness of monitoring rehabilitation training is brought through the respiratory belt.
基金The work is supported in part by the National Natural Science Foundation of China under Grants(61873304)in part by the China Postdoctoral Science Foundation Funded Project under Grant(2018M641784)also in part by the Funding of Jilin Province Science and Technology(JJKH20210745KJ).
文摘This paper introduces a rigid-flexible coupling wearable exoskeleton robot for lower limb,which is designed in light of gait biomechanics and beneficial for low limb movement disorders by implementing gait training.The rationality of the proposed mechanism is shown with the implementation of the dynamic simulation through MSC ADAMS.For the purposes of lightweight,the exoskeleton mechanism is optimized through finite element analysis.It can be concluded from performance evaluation experiment,the mechanism has certain advantages over existing exoskeleton robots,namely,comfortable,lightweight,low cost,which can be utilized for rehabilitation training in medical institutions or as a daily-walking ancillary equipment for patients.
