Optimal design of tricept parallel manipulator with particle swarm optimization using performance parameters

Abstract

The parallel manipulators are skilled for their precision manufacturing but need optimized design to get maximum dexterity that will lead towards better industrial production rates. The 3-DOF tricept is chosen to utilize its maximum capabilities for its functionality. Three performance parameters conditioning index, workspace volume, and global conditioning index are used to obtain optimum design variables of tricept mechanism. With a view to compare them in terms of processing effort, particle swarm optimization (PSO) is applied here. Finally, multiobjective optimization with two strategies weighted and epsilon constraint is performed to control the different parameters simultaneously and also to give validation of previously obtained GA based optimum design values of tricept mechanism.