TY - JOUR
T1 - Research on synchronization of cooperative trajectory of dual industrial robots based on fuzzy adaptive PID control strategy
AU - Xiong, Qiang
AU - Wang, Jianqun
N1 - Publisher Copyright:
© 2022 Institute of Physics Publishing. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Through the research on the synchronization of the cooperative trajectory of dual industrial robots, this paper analyses the characteristics of master-slave control and distributed control, and puts forward a fuzzy adaptive PID control method suitable for the cooperative scene of dual industrial robots, which can dynamically adjust the parameters of PID control online and adapt the dynamic system of industrial robots in real time. Taking two same 6-DOF ABB industrial robots as examples, common PID controller and fuzzy PID controller are compared and simulated under master-slave control mode and distributed control mode respectively. The simulation results verified that the fuzzy adaptive PID control method is effective, and the distributed control mode has more applicability and expansibility than the master-slave control mode.
AB - Through the research on the synchronization of the cooperative trajectory of dual industrial robots, this paper analyses the characteristics of master-slave control and distributed control, and puts forward a fuzzy adaptive PID control method suitable for the cooperative scene of dual industrial robots, which can dynamically adjust the parameters of PID control online and adapt the dynamic system of industrial robots in real time. Taking two same 6-DOF ABB industrial robots as examples, common PID controller and fuzzy PID controller are compared and simulated under master-slave control mode and distributed control mode respectively. The simulation results verified that the fuzzy adaptive PID control method is effective, and the distributed control mode has more applicability and expansibility than the master-slave control mode.
UR - http://www.scopus.com/inward/record.url?scp=85142480894&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/2365/1/012037
DO - 10.1088/1742-6596/2365/1/012037
M3 - Conference article
AN - SCOPUS:85142480894
SN - 1742-6588
VL - 2365
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012037
T2 - 2022 3rd International Conference on Internet of Things, Artificial Intelligence and Mechanical Automation, IoTAIMA 2022
Y2 - 22 July 2022 through 24 July 2022
ER -