This paper studies the vibration control effect for manipulators with both flexible link and flexible joint according to the energy-vibration-optimal (EVO) trajectory planning method effect by the constraint conditions and structure parameters. First, a dynamic model of the flexible joint-flexible link arm is established following the assumed modal method and Lagrange principle. The optimization model is then proposed and discretized using the Particle Swarm Optimization (PSO) trajectory planning method and the trajectory optimization of discrete result algorithm, taking into account both residual oscillation and energy consumption. Following that, the numerical trajectory optimization results and their vibration suppression effect analysis by different constraint conditions, such as driving constraints, time constraints, and joint stiffness, are compared and discussed. The results show that the optimization velocity trajectory tends to a S-shaped trajectory and a convex trajectory respectively with the increase of driving velocity constraint and acceleration constraint respectively, while the sufficient planning time can make the less energy consumption. The parameter variations of length, cross-sectional area and next link lumped mass of have a significant impact on the residual oscillation of the flexible arm, with length having the most influence, whereas joint stiffness has little influence on the residual oscillation of the flexible link. The processing accuracy of length, cross-sectional area and end quality parameters must be ensured, while joint stiffness accuracy requirements can be slightly relaxed during the actual processing. Finally, experiments show that the optimization method is effective at vibration suppression. While the small variations of the end mass have significant influence on the vibration suppression effect, the residual vibrations of the parameter variation ones are all larger than the original parameter one. Meanwhile, as the mass of the manipulator increases, so does its energy consumption.
Read full abstract