To improve the stability of underactuated robotic arms in the sorting process of fragile parts,a fuzzy PID control algorithm is proposed to optimize their grasping performance by im-proving the particle swarm algorithm.Firstly,the characteristics of the underactuated robotic arm grasping force control system were analyzed and a specific strategy was proposed that com-bines particle swarm algorithm optimization algorithm with fuzzy PID grasping force control sys-tem.Secondly,methods such as dynamic inertia weights were introduced into particle swarm al-gorithm to improve its iteration speed and avoid falling into local optima.On this basis,the im-proved particle swarm optimization algorithm was used to optimize the relevant parameters of the fuzzy PID controller,achieving online self-tuning of fuzzy rule weights and quantization factors,and solving the problem of PID parameters unable to be dynamically adjusted.Finally,the meth-od was simulated and analyzed.The results show that the control algorithm designed in this pa-per can achieve stable grasping force within 0.8 s,with a steady-state error of less than 0.2％,and a disturbance tuning time of 0.262 s.The transient response speed,control accuracy,and stability of the system are significantly improved.
关键词
零件分拣/抓取力控制/改进粒子群算法/模糊PID控制/欠驱动机械手
Key words
part sorting/grasping force control/improve particle swarm optimization algorithm/fuzzy PID control/underactuated robotic arm
维普
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