Purpose–The purpose of this paper is to apply a intelligent algorithm to conduct the force tracking control for electrohydraulic servo system(EHSS).Specifically,the adaptive neuro-fuzzy inference system(ANFIS)is sele...Purpose–The purpose of this paper is to apply a intelligent algorithm to conduct the force tracking control for electrohydraulic servo system(EHSS).Specifically,the adaptive neuro-fuzzy inference system(ANFIS)is selected to improve the control performance for EHSS.Design/methodology/approach–Two types of input–output data were chosen to train the ANFIS models.The inputs are the desired and actual forces,and the output is the current.The first type is to set a sinusoidal signal for the current to produce the actual driving force,and the desired force is chosen as same as the actual force.The other type is to give a sinusoidal signal for the desired force.Under the action of the PI controller,the actual force tracks the desired force,and the current is the output of the PI controller.Findings–The models built based on the two types of data are separately named as the ANFIS I controller and the ANFIS II controller.The results reveal that the ANFIS I controller possesses the best performance in terms of overshoot,rise time and mean absolute error and show adaptivity to different tracking conditions,including sinusoidal signal tracking and sudden change signal tracking.Originality/value–This paper is the first time to apply the ANFIS to optimize the force tracking control for EHSS.展开更多
In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of ...In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.展开更多
基金This work was supported by the National Key R&D Program of China“The study on Load-bearing and Moving Support Exoskeleton Robot Key Technology and Typical Application”(2017YFB1300502)This work is also supported by the National Natural Science Foundation of China“Research on gait detection and recognition technology of Parkinson’s disease based on all-fiber composite sensors”under Grant 61903280Hubei Key Laboratory of Digital Textile Equipment Open fund“Research on intelligent monitoring clothing based on micro-nano fiber composite sensor”under Grant DTL2019011.
文摘Purpose–The purpose of this paper is to apply a intelligent algorithm to conduct the force tracking control for electrohydraulic servo system(EHSS).Specifically,the adaptive neuro-fuzzy inference system(ANFIS)is selected to improve the control performance for EHSS.Design/methodology/approach–Two types of input–output data were chosen to train the ANFIS models.The inputs are the desired and actual forces,and the output is the current.The first type is to set a sinusoidal signal for the current to produce the actual driving force,and the desired force is chosen as same as the actual force.The other type is to give a sinusoidal signal for the desired force.Under the action of the PI controller,the actual force tracks the desired force,and the current is the output of the PI controller.Findings–The models built based on the two types of data are separately named as the ANFIS I controller and the ANFIS II controller.The results reveal that the ANFIS I controller possesses the best performance in terms of overshoot,rise time and mean absolute error and show adaptivity to different tracking conditions,including sinusoidal signal tracking and sudden change signal tracking.Originality/value–This paper is the first time to apply the ANFIS to optimize the force tracking control for EHSS.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB3403402)National Natural Science Foundation of China Basic Research Programme for PhD Students(Grant No.524B2049)。
文摘In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.
