This study proposed a force and shape collaborative control method that combined method of influence coefficients(MIC)and the elitist nondominated sorting genetic algorithm(NSGA-II)to reduce the shape deviation caused...This study proposed a force and shape collaborative control method that combined method of influence coefficients(MIC)and the elitist nondominated sorting genetic algorithm(NSGA-II)to reduce the shape deviation caused by manufacturing errors,gravity deformation,and fixturing errors and improve the shape accuracy of the assembled large composite fuselage panel.This study used a multi-point flexible assembly system driven by hexapod parallel robots.The proposed method simultaneously considers the shape deviation and assembly load of the panel.First,a multi-point flexible assembly system driven by hexapod parallel robots was introduced,with the relevant variables defined in the control process.In addition,the corresponding mathematical model was constructed.Subsequently,MIC was used to establish the prediction models between the displacements of actuators and displacements of panel shape control points,deformation loads applied by the actuators.Following the modeling,the shape deviation of the panel and the assembly load were used as the optimization objectives,and the displacements of actuators were optimized using NSGA-II.Finally,a typical composite fuselage panel case study was considered to demonstrate the effectiveness of the proposed method.展开更多
基金supported by National Natural Science Foundation of China(No.52105502)Fund of National Engineering and Research Center for Commercial Aircraft Manufacturing(Nos.COMAC-SFGS-2019-263 and COMAC-SFGS-2019-3731)the Fundamental Research Funds for the Central Universities(No.3042021601).
文摘This study proposed a force and shape collaborative control method that combined method of influence coefficients(MIC)and the elitist nondominated sorting genetic algorithm(NSGA-II)to reduce the shape deviation caused by manufacturing errors,gravity deformation,and fixturing errors and improve the shape accuracy of the assembled large composite fuselage panel.This study used a multi-point flexible assembly system driven by hexapod parallel robots.The proposed method simultaneously considers the shape deviation and assembly load of the panel.First,a multi-point flexible assembly system driven by hexapod parallel robots was introduced,with the relevant variables defined in the control process.In addition,the corresponding mathematical model was constructed.Subsequently,MIC was used to establish the prediction models between the displacements of actuators and displacements of panel shape control points,deformation loads applied by the actuators.Following the modeling,the shape deviation of the panel and the assembly load were used as the optimization objectives,and the displacements of actuators were optimized using NSGA-II.Finally,a typical composite fuselage panel case study was considered to demonstrate the effectiveness of the proposed method.
