Parameter optimization of the controllable local degree of freedom is studied for reducing vibration of the flexible manipulator at the lowest possible cost. The controllable local degrees of freedom are suggested and introduced to the topological structure of the flexible manipulator, and used as an effective way to alleviate vibration through dynamic coupling. Parameters introduced by the controllable local degrees of freedom are analyzed and their influences on vibration reduction are investigated. A strategy to optimize these parameters is put forward and the corresponding optimization method is suggested based on Particle Swarm Optimization （PSO）. Simulations are conducted and results of case studies confirm that the proposed optimization method is effective in reducing vibration of the flexible manipulator at the lowest possible cost.
When performing operation tasks, the interaction between a flexible manipulator and a grasped object usually results in an impact. In this paper, a new way is suggested to alleviate impact vibration of a flexible manipulator via its structural characteristic when capturing a moving object. Controllable local degrees of freedom are introduced to the topological structure of the flexible manipulator, and used as an effective tool to combat impact vibration through dynamic coupling. A corresponding method is put forward to reduce impact vibration responses of the flexible manip- ulator via the controllable local degrees of freedom. By planning motion of the controllable local degrees of freedom, appropriate control force can be constructed to increase the modal damping and stiffness and eliminate the exciting force simultaneously, thereby reducing impact vibration responses of the flexible manipulator. Simulations are conducted and results are shown to prove the presented method.
To improve the grinding quality of robotic belt grinding systems for the workpieces with complex shaped surfaces, new concepts of the dexterity grinding point and the dexterity grinding space are proposed and their mathematical descriptions are defined. Factors influencing the dexterity grinding space are analyzed. And a method to determine the necessary dexterity grinding space is suggested. Based on particle swarm optimization （PSO） method, a strategy to optimize the grinding robot structural dimensions and position with respect to the grinding wheel is put forward to obtain the necessary dexterity grinding space. Finally, to grind an aerial engine blade, a dedicated PPPRRR （P： prismatic R： rotary） grinding robot structural dimensions and position with respect to the grinding wheel are optimized using the above strategy. According to simulation results, if the blade is placed within the dexterity grinding space, only one gripper and one grinding machine are needed to grind its complex shaped surfaces.
