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Mathematical model analysis of an intelligent control system for open architecture robots.

Authors :
Qin, Chunbin
Zheng, Yanjun
Basu, M.A.
Fernández-Martínez, Manuel
Guirao, Juan L.G.
Source :
Journal of Intelligent & Fuzzy Systems. 2018, Vol. 35 Issue 4, p4455-4464. 10p.
Publication Year :
2018

Abstract

At present, the intelligent control system of robots is closed, which has the disadvantages of poor fault tolerance, unstable operation and low positioning accuracy. Aiming at these deficiencies, a Petri net model of the intelligent control system for open architecture robots based on PMAC is designed. Starting from the kinematics of robots, the forward and inverse kinematics model of open architecture robots are established according to DH method; then the trajectory planning is performed from Cartesian space linear interpolation algorithm and circular interpolation algorithm respectively, and the basic function of robot path planning is constructed. Finally, a PMAC-based open architecture robot intelligent control system is established. The control system adopts dual-microcomputer hierarchical control mode and modular structure design. Real-time communication between the upper computer and the lower computer can be realized by calling the Pcomm32 dynamic link library; based on the robot's forward and inverse kinematics model and trajectory interpolation algorithm, the modular control software for the robot system is developed. The control software realizes functions such as security check, parameters setting, kinematics analysis, and teaching reproduction. Combined with the principle of hierarchical Petri nets, various modules of open architecture robot control system based on PMAC are modeled. Experiments show that the designed system runs smoothly, has high positioning accuracy, good openness and scalability. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10641246
Volume :
35
Issue :
4
Database :
Academic Search Index
Journal :
Journal of Intelligent & Fuzzy Systems
Publication Type :
Academic Journal
Accession number :
132752744
Full Text :
https://doi.org/10.3233/JIFS-169764