Comparative Study Methods of Trajectory Tracking Control for Robot Manipulator.

Authors

R. Hassan, Assistant lecturer, Electrical Engineering Department, Faculty of Engineering, Suez Canal University, Ismailia, EgyptFollow
F. Bendary, Professor, Electrical Engineering Department, Faculty of Engineering, Benha University, Shobra , EgyptFollow
K. Elserafi, Associate Professor, Electrical Engineering Department, Faculty of Engineering, Port Said University, Port Said, EgyptFollow
A. Ghanem, Doctorate Engineer, Electrical Engineering Department, Faculty of Engineering, Suez Canal University, Shobra, Ismailia, EgyptFollow
M. Soliman, Doctorate Engineer, Electrical Engineering Department, Faculty of Engineering, Benha University, Shobra, EgyptFollow

Corresponding Author

Hassan, R.

Subject Area

Electrical Engineering

Article Type

Original Study

Abstract

In this article a three non-model based trajectory tracking controllers for rigid simple open chain robot manipulator are investigated. The first is a Fuzzy-PID controller, it is considered as a reference benchmark to compare its results with the others which are a proportional Derivative (PD) tuned using genetic algorithm (GA) and an Adaptive Neuro Fuzzy Inference System (ANFIS). The simulation is carried out for the first three joints of robot arm (PUMA560) aiming to track aquintic polynomial trajectory with minimum errors, and good disturbance rejection. Simulation results, shows that using Fuzzy-PID has better steady state error and RMS error than the ANFIS and PD tuned using GA. The three controllers are tested by simulated under the same conditions using SIMULINK under MATLAB2013a.

Keywords

PUMA560; Trajectories planning; Proportional Derivative (PD) controller; Adaptive Neuro Fuzzy Inference System (ANFIS); Fuzzy-PID controller

Recommended Citation

Hassan, R.; Bendary, F.; Elserafi, K.; Ghanem, A.; and Soliman, M. (2020) "Comparative Study Methods of Trajectory Tracking Control for Robot Manipulator.," Mansoura Engineering Journal: Vol. 40 : Iss. 4 , Article 1.
Available at: https://doi.org/10.21608/bfemu.2020.101868