Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employe...Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.展开更多
Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that ca...Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that can be adjusted according to pressure feedback,thus enabling it to adapt to various body shapes.To improve the force tracking accuracy and prevent obvious force overshoot in the initial contact stage,a contact force control strategy based on fuzzy adaptive variable impedance is proposed.The proposed contact force control strategy achieves an average root-mean-square error of 0.024 and an average overshoot of 1.74%.Experimental results demonstrate that the designed deformable shield can fit the human body well,while the proposed control strategy enhances the contact force management and realizes the precise control of human-robot contact force.展开更多
An automatic navigation system was developed to realize automatic driving for combine harvester,including the mechanical design,control method and software design.First of all,for the harvester modified with the autom...An automatic navigation system was developed to realize automatic driving for combine harvester,including the mechanical design,control method and software design.First of all,for the harvester modified with the automatic navigation system,a dynamic calibration method of the rear wheel center position was proposed.The control part included the navigation controller and the steering controller.A variable universe fuzzy controller was designed to the navigation controller,which used fuzzy control to change the fuzzy universe of input and output dynamically,that means,under the condition that the fuzzy rules remain unchanged,the fuzzy universe changes with the change of input,which is an adaptive fuzzy control method and can modify the control strategy in time.To realize the automatic navigation of the harvester,the decision result of the navigation controller based on the variable universe fuzzy control was input into the steering controller,and then the electric steering wheel was controlled to rotate.To test the performance of the designed automatic navigation system,the field experiment was carried out.When the combine harvester was navigating linearly at a speed of 0.8 m/s,the overall root mean square error(RMSE)of the lateral deviation was 5.87 cm.The test results showed that the system was designed could make the combine track the preset path smoothly and stably,and the tracking accuracy was at the centimeter level.展开更多
基金Project(60634020) supported by the National Natural Science Foundation of China
文摘Based on consideration of the differential relations between the immeasurable variables and measurable variables in electro-hydraulic servo system,adaptive dynamic recurrent fuzzy neural networks(ADRFNNs) were employed to identify the primary uncertainty and the mathematic model of the system was turned into an equivalent linear model with terms of secondary uncertainty.At the same time,gain adaptive sliding mode variable structure control(GASMVSC) was employed to synthesize the control effort.The results show that the unrealization problem caused by some system's immeasurable state variables in traditional fuzzy neural networks(TFNN) taking all state variables as its inputs is overcome.On the other hand,the identification by the ADRFNNs online with high accuracy and the adaptive function of the correction term's gain in the GASMVSC make the system possess strong robustness and improved steady accuracy,and the chattering phenomenon of the control effort is also suppressed effectively.
基金supported by grants from the National Key R and D Program of China(2022YFB4703300).
文摘Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that can be adjusted according to pressure feedback,thus enabling it to adapt to various body shapes.To improve the force tracking accuracy and prevent obvious force overshoot in the initial contact stage,a contact force control strategy based on fuzzy adaptive variable impedance is proposed.The proposed contact force control strategy achieves an average root-mean-square error of 0.024 and an average overshoot of 1.74%.Experimental results demonstrate that the designed deformable shield can fit the human body well,while the proposed control strategy enhances the contact force management and realizes the precise control of human-robot contact force.
基金supported by the National Key Research and Development Program(Grant No.2019YFB1312300-2019YFB1312305)National Key Research and Development Program of China(Grant No.2017YFD0700400-2017YFD0700403)+1 种基金the National Natural Science Foundation of China(Grant No.31571570)CAU special fund to build world-class university(in disciplines)and guide distinctive development(2021AC006).
文摘An automatic navigation system was developed to realize automatic driving for combine harvester,including the mechanical design,control method and software design.First of all,for the harvester modified with the automatic navigation system,a dynamic calibration method of the rear wheel center position was proposed.The control part included the navigation controller and the steering controller.A variable universe fuzzy controller was designed to the navigation controller,which used fuzzy control to change the fuzzy universe of input and output dynamically,that means,under the condition that the fuzzy rules remain unchanged,the fuzzy universe changes with the change of input,which is an adaptive fuzzy control method and can modify the control strategy in time.To realize the automatic navigation of the harvester,the decision result of the navigation controller based on the variable universe fuzzy control was input into the steering controller,and then the electric steering wheel was controlled to rotate.To test the performance of the designed automatic navigation system,the field experiment was carried out.When the combine harvester was navigating linearly at a speed of 0.8 m/s,the overall root mean square error(RMSE)of the lateral deviation was 5.87 cm.The test results showed that the system was designed could make the combine track the preset path smoothly and stably,and the tracking accuracy was at the centimeter level.
