Trajectory planning of vibration suppression for hybrid structure flexible manipulator based on differential evolution particle swarm optimization algorithm

Abstract

Abstract A differential evolution particle swarm optimization algorithm is proposed to address the vibration problem of a hybrid structure flexible manipulator after motion and stop. Firstly, the errors in the modeling process of the flexible manipulator were corrected, and its state variables were decomposed to establish dynamic and kinematic models. A sliding mode controller was then designed to track the trajectory. To find the optimal trajectory, a mapping function was constructed, and non-uniform interpolation points were selected. A normal distribution function was used to select discrete interpolation points, and the cubic spline interpolation was used to fit the trajectory. To prevent the particle swarm optimization algorithm from falling into local optima, the mutation and crossover operators of the differential evolution algorithm are incorporated into the algorithm, thereby expanding the search range. The effectiveness of this improved method was verified by comparing it with traditional particle swarm optimization algorithms. This study provides a new trajectory planning approach for the motion control of a hybrid structured flexible manipulator and has important practical significance.