Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of i...Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to construct.Hence,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model parameters.Meanwhile,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical constraints.Then a backstepping controller based on the identified model is adopted to improve the human-robot wearable comfortable performance under cooperative motion.Finally,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons platform.The knee joint motion achieves a steady-state response after 0.5 s.Meanwhile,the position error of hip joint response is less than 0.03 rad after 0.9 s.In addition,the steady-state human-robot interaction torque of the two joints is constrained within 15 N·m.This research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model parameters.Furthermore,an enhanced mutation strategy is adopted to avoid whale evolution’s unsatisfactory local optimal value.展开更多
In this study,a humanoid prototype of 2-DOF(degrees of freedom)lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton.To improve the detection accuracy of the h...In this study,a humanoid prototype of 2-DOF(degrees of freedom)lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton.To improve the detection accuracy of the humanrobot interaction torque,a BPNN(backpropagation neural networks)is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor.Meanwhile,the backstepping controller is designed to realize the exoskeleton's passive position control,which means that the person passively adapts to the exoskeleton.On the other hand,a variable admittance controller is used to implement the exoskeleton's active followup control,which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance.To improve the wearable comfortable effect,serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters.Finally,the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.展开更多
For the 2-Degree of Freedom(DOF)lower limb exoskeleton,to ensure the system robustness and dynamic performance,a linearextended-state-observer-based(LESO)robust sliding mode control is proposed to not only reduce the ...For the 2-Degree of Freedom(DOF)lower limb exoskeleton,to ensure the system robustness and dynamic performance,a linearextended-state-observer-based(LESO)robust sliding mode control is proposed to not only reduce the influence of parametric uncertainties,unmodeled dynamics,and external disturbance but also estimate the unmeasurable real-time joint angular velocity directly.Then,via Lyapunov technology,the stability of the corresponding LESO and controller is proven.The appropriate and reasonable simulation was carried out to verify the effectiveness of the proposed LESO and exoskeleton controller.展开更多
Flow velocity plays an important role in recirculating aquaculture systems(RAS)and the growing practice of culturing juvenile largemouth bass(Micropterus salmoides).In this study,the effects of flow velocity on the wa...Flow velocity plays an important role in recirculating aquaculture systems(RAS)and the growing practice of culturing juvenile largemouth bass(Micropterus salmoides).In this study,the effects of flow velocity on the water quality as well as the ammonia excretion were discussed from the perspective of actual production,and a polynomial model of ammonia nitrogen excretion was established,using the juvenile largemouth bass.Results showed that the range of ammonia nitrogen and nitrite nitrogen decreased with flow velocity increasing,while the number and volume share of large particles increased.According to the polynomial model,compared with the medium flow velocity(11 cm/s,2.45 body length(bl)/s),the ammonia excretion of juvenile largemouth bass at high(18 cm/s,4.00 bl/s),and low(4 cm/s,0.90 bl/s)flow velocity changed faster with time,and the excretion rate peaked at the 6th hour after feeding,earlier than that under medium flow velocity.Therefore,it is suggested to increase the flow velocity at the 5th hour after feeding and then decreased it at the 10th hour,to ensure better water quality in RAS culturing juvenile largemouth bass.展开更多
基金Supported by National Key Research and Development Program of China(Grant No.2022YFF0708903)Ningbo Municipal Key Technology Research and Development Program of China(Grant No.2022Z006)Youth Fund of National Natural Science Foundation of China(Grant No.52205043)。
文摘Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to construct.Hence,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model parameters.Meanwhile,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical constraints.Then a backstepping controller based on the identified model is adopted to improve the human-robot wearable comfortable performance under cooperative motion.Finally,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons platform.The knee joint motion achieves a steady-state response after 0.5 s.Meanwhile,the position error of hip joint response is less than 0.03 rad after 0.9 s.In addition,the steady-state human-robot interaction torque of the two joints is constrained within 15 N·m.This research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model parameters.Furthermore,an enhanced mutation strategy is adopted to avoid whale evolution’s unsatisfactory local optimal value.
基金Supported by National Natural Science Foundation of China(Grant Nos.51775089,12072068,11872147)Sichuan Province Science and Technology Support Program of China(Grant Nos.2020YFG0137,2018JY0565).
文摘In this study,a humanoid prototype of 2-DOF(degrees of freedom)lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton.To improve the detection accuracy of the humanrobot interaction torque,a BPNN(backpropagation neural networks)is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor.Meanwhile,the backstepping controller is designed to realize the exoskeleton's passive position control,which means that the person passively adapts to the exoskeleton.On the other hand,a variable admittance controller is used to implement the exoskeleton's active followup control,which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance.To improve the wearable comfortable effect,serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters.Finally,the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.
基金This work was supported by National Natural Science Foundation of China(No.51775089 and 11872147)Sichuan Science and Technology Program(No.2018JY0565 and 2020YFG0137).
文摘For the 2-Degree of Freedom(DOF)lower limb exoskeleton,to ensure the system robustness and dynamic performance,a linearextended-state-observer-based(LESO)robust sliding mode control is proposed to not only reduce the influence of parametric uncertainties,unmodeled dynamics,and external disturbance but also estimate the unmeasurable real-time joint angular velocity directly.Then,via Lyapunov technology,the stability of the corresponding LESO and controller is proven.The appropriate and reasonable simulation was carried out to verify the effectiveness of the proposed LESO and exoskeleton controller.
基金financially supported by the Open Fund of Zhejiang Institute of Freshwater Fisheries(Grant No.ZJK201905)the Key R&D Program of Zhejiang Province,China(Grant No.2021C02024,2019C02082)the Technology Program of the Department of Agriculture and Rural Areas of Zhejiang Province,China(Grant No.2020XTTGSC01).
文摘Flow velocity plays an important role in recirculating aquaculture systems(RAS)and the growing practice of culturing juvenile largemouth bass(Micropterus salmoides).In this study,the effects of flow velocity on the water quality as well as the ammonia excretion were discussed from the perspective of actual production,and a polynomial model of ammonia nitrogen excretion was established,using the juvenile largemouth bass.Results showed that the range of ammonia nitrogen and nitrite nitrogen decreased with flow velocity increasing,while the number and volume share of large particles increased.According to the polynomial model,compared with the medium flow velocity(11 cm/s,2.45 body length(bl)/s),the ammonia excretion of juvenile largemouth bass at high(18 cm/s,4.00 bl/s),and low(4 cm/s,0.90 bl/s)flow velocity changed faster with time,and the excretion rate peaked at the 6th hour after feeding,earlier than that under medium flow velocity.Therefore,it is suggested to increase the flow velocity at the 5th hour after feeding and then decreased it at the 10th hour,to ensure better water quality in RAS culturing juvenile largemouth bass.
