Vol. 21 No. 1 (2018) Cover Image
Vol. 21 No. 1 (2018)

Published: February 28, 2018

Pages: 1-11

Articles

Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot

Mohammed Y. Hassan 1 Athraa Faraj Sugban 1
1 Control and Systems Eng. Dep., University of Technology
History
  • Received: February 12, 2017
  • Revised: May 21, 2017
  • Accepted: November 16, 2017
  • Available Online: February 10, 2018
DOI

https://doi.org/10.29194/NJES21010001

Abstract

This paper proposes the design and simulation of Interval Type-2 Fuzzy Logic Control using MATLAB/Simulink to control the position of the bucket of the backhoe excavator robot during digging operations. In order to reach accurate position responses with minimum overshoot and minimum steady state error, Ant Colony Optimization (ACO) algorithm is used to tune the gains of the position and force parts for the force-position controllers to obtain the best position responses. The joints are actuated by the electro-hydraulic actuators. The force-position control incorporating two-Mamdani type-Proportional-Derivative-Interval Type-2 Fuzzy Logic Controllers for position control and 3-Proportional-Derivative Controllers for force control. The nonlinearity and uncertainty in the model that inherit in the electro hydraulic actuator system are also studied. The nonlinearity includes oil leakage and frictions in the joints. The friction model is represented as a Modified LuGre friction model in actuators. The excavator robot joints are subjected to Coulomb, viscous and stribeck friction. The uncertainty is represented by the variation of bulk modulus. It can be shown from the results that the ACO obtain the best gains of the controllers which enhances the position responses within the range of (19, 23 %) compared with the controllers tuned manually.

Keywords

References

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