Abstract
The strong dynamic coupling effects among kinematic chains are not beneficial to the control of parallel mechanisms. This paper deals with the chain position optimization of a 4UPS−UPU parallel mechanism to reduce dynamic coupling effects among kinematic chains. Using the kinematic model, the Jacobian matrix is derived, and a method is proposed to transform it into a non-dimensional form and being independent of scaling factors. A singularity index is formulated based on the normalized determinant of the modified Jacobian matrix, guiding the optimization of chain positions at the base platform. Subsequently, the dynamic model is derived by using the principle of virtual work and a novel dynamic coupling index is proposed by taking both the inertia and centrifugal terms in the dynamic model into account. The neural network is then employed to enhance the calculation efficiency of the dynamic coupling index. Finally, the chain positions at the moving platform are optimized using Particle Swarm Optimization algorithm. This optimization process significantly reduces the dynamic coupling effects among kinematic chains in the parallel mechanism, thereby conferring advantageous benefits to its overall control.
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