改进粒子群算法的单杆柔性臂振动抑制方法研究OA北大核心CSTPCD

When using traditional linear quadratic regulator(LQR)method to control flexible manipulator,the weighted matrix is usually chosen based on prior knowledge.The particle swarm algorithm can independently to find the optimal solution through iterative operation,but the convergence speed of traditional particle swarm optimization(PSO)algorithm is relatively slow.This article proposes an improved particle swarm algorithm to optimize the weighted matrix of LQR control method.The dynamics equation of the flexible manipulator is established by Lagrange equation,and its control model is deduced based on LQR.Based on the traditional particle swarm optimization(PSO),the crossover operation and nonlinear dynamic inertial weight are introduced to improve the global and local search capability.Finally,the comparison and analysis of controlled flexible manipulator simulation results show that the improved PSO algorithm has faster convergence speed and better vibration suppression effect than the traditional PSO algorithm,which provides assistance and support for manipulator's higher precision applications.