基于PSO算法优化模糊PID控制器的灵巧手抓取控制研究  

Research on grasp control of smart hand optimization using fuzzy PID controller based on PSO algorithm

作　　者：李锦洋 关翔予 孔晓光[1] 许舜 LI Jinyang;GUAN Xiangyu;KONG Xiaoguang;XU Shun(Shenyang University of Chemical Technology,Liaoning Shenyang 110000,China;Xiaomi Technology Co.,Ltd.Nanjing Branch,Jiangsu Nanjing 210000,China)

机构地区：[1]沈阳化工大学,辽宁沈阳110000 [2]小米科技(南京)有限公司,江苏南京210000

出　　处：《工业仪表与自动化装置》2024年第2期75-79,共5页Industrial Instrumentation & Automation

摘　　要：随着仿生学的进展,机器人领域中五指灵巧手作为主要执行机构的重要性不断增强。然而,在抓取过程中,五指灵巧手常常面临内部作用复杂、速度缓慢和效率低等问题。为了应对这些挑战,该文提出了一种基于角度闭环模糊自适应控制算法。该算法采用模糊策略来推断灵巧手关节角度偏差与控制器参数之间的关系,并制定相应的模糊规则。通过实时调整控制器参数,该算法能够提高系统的稳定性和抓取效率。此外,通过建立ADAMS模型和相应的闭环控制系统,以提高实验过程的可视化程度。实验结果表明,通过采用粒子群算法(Particle Swarm Optimization Algorithm)优化模糊自适应PID算法并改进系统参数,相较于传统的PID算法,可以显著减少灵巧手在抓取过程中的关节抖动,并展现出更好的手指指尖接触力控制性能。With the increasing importance of bionics,the five-finger dexterous hand has become a crucial executive mechanism in the field of robotics.However,during the grasping process,the five-finger dexterous hand often encounters challenges such as complex internal actions,slow speed,and low efficiency.In order to overcome these issues,this paper proposes a fuzzy adaptive control algorithm based on angle closed-loop.The algorithm utilizes fuzzy logic to infer the relationship between the angle deviation of the dexterous hand joint and the controller parameters,and formulates corresponding fuzzy rules.By adjusting the controller parameters in real time,the algorithm improves the stability and capture efficiency of the system.Additionally,the visualization of the experimental process is enhanced by establishing an ADAMS model and a corresponding closed-loop control system.Experimental results demonstrate that optimizing the fuzzy adaptive PID algorithm and improving the system parameters of the Particle Swarm Optimization algorithm can significantly reduce joint jitter during the grasping process of dexterous hands,while also exhibiting superior fingertip contact force control performance.

关 键 词：灵巧手 模糊控制 PID算法 粒子群算法 

分 类 号：TP241.3[自动化与计算机技术—检测技术与自动化装置]