Trajectory tracking control of a 6-DOF robotic arm based on improved FOPID

被引:0
作者
Jiang, Zhou [1 ]
Zhang, Xiaohua [2 ]
Liu, Guoquan [3 ]
机构
[1] Anhui Automobile Vocat & Tech Coll, Dept Mech & Elect Engn, Hefei 230601, Anhui, Peoples R China
[2] Zhongkai Univ Agr & Engn, Coll Automat, Guangzhou 510225, Guangdong, Peoples R China
[3] East China Univ Technol, Sch Mech & Elect Engn, Guanglan Ave 418, Nanchang 330013, Peoples R China
关键词
6-DOF robotic arm; Trajectory tracking; Optimization algorithm; FOPID controller; OPTIMIZATION; SYSTEM; DESIGN;
D O I
10.1007/s40435-025-01620-x
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Robotic arm is a complex system with multiple inputs and outputs, strong nonlinearity and strong coupling, and the research of high precision trajectory tracking control technology for robotic arm has been an important issue for scholars at home and abroad. This paper takes the six-degree-of-freedom (6-DOF) robotic arm as its study object and designs a fractional-order PID (FOPID) control method. To improve its control accuracy, a parameter tuning method of fractional-order beetle antennae particle swarm algorithm (FBPA) optimized FOPID controller is proposed. This method puts the beetle antennae search (BAS) algorithm together with the particle swarm optimization (PSO) algorithm, introduces the concept of fractional-order calculus into the algorithm, dynamically adjusts the inertial weights and fractional order and finally improves the optimization effect of the algorithm. The simulation experiments of MATLAB/Simulink indicate that in comparison with the traditional PID control method, the FOPID control method optimized by the FBPA has high control accuracy and small overshooting, which meets the high-precision control requirements of the 6-DOF robotic arm.
引用
收藏
页数:14
相关论文
共 31 条
[1]   FOPID controller with fractional filter for an automatic voltage [J].
Ayas, Mustafa Sinasi ;
Sahin, Erdinc .
COMPUTERS & ELECTRICAL ENGINEERING, 2021, 90
[2]   PID sliding surface-based adaptive dynamic second-order fault-tolerant sliding mode control design and experimental application to an electromechanical system [J].
Aydin, Merve Nilay ;
Coban, Ramazan .
INTERNATIONAL JOURNAL OF CONTROL, 2022, 95 (07) :1767-1776
[3]   Cooperative Underwater Vehicle-Manipulator Operation Using Redundant Resolution Method [J].
Bae, Jangho ;
Moon, Yecheol ;
Park, Eugene ;
Kim, Jongwon ;
Jin, Sangrok ;
Seo, TaeWon .
INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, 2022, 23 (09) :1003-1017
[4]   A novel vision-based calibration framework for industrial robotic manipulators [J].
Balanji, Hamid Majidi ;
Turgut, Ali Emre ;
Tunc, Lutfi Taner .
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING, 2022, 73
[5]   A review of PID control, tuning methods and applications [J].
Borase, Rakesh P. ;
Maghade, D. K. ;
Sondkar, S. Y. ;
Pawar, S. N. .
INTERNATIONAL JOURNAL OF DYNAMICS AND CONTROL, 2021, 9 (02) :818-827
[6]   Optimal Trajectory Generation for a 6-DOF Parallel Manipulator Using Grey Wolf Optimization Algorithm [J].
Choubey, Chandan ;
Ohri, Jyoti .
ROBOTICA, 2021, 39 (03) :411-427
[7]   Novel fractional order particle swarm optimization [J].
Couceiro, Micael ;
Sivasundaram, Seenith .
APPLIED MATHEMATICS AND COMPUTATION, 2016, 283 :36-54
[8]  
Dengler N, 2022, IEEE INT C INT ROBOT
[9]   Trajectory planning and tracking control for 6-DOF Stanford manipulator based on adaptive sliding mode multi-stage switching control [J].
Hu, Qingxi ;
Zhang, Dianfeng ;
Wu, Zhaojing .
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, 2021, 31 (14) :6602-6625
[10]  
Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968