Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot
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 err...
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| Format: | Article |
| Language: | English |
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Al-Nahrain Journal for Engineering Sciences
2018-02-01
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| Series: | مجلة النهرين للعلوم الهندسية |
| Subjects: | |
| Online Access: | https://nahje.com/index.php/main/article/view/367 |
| _version_ | 1818950239975899136 |
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| author | Mohammed Y. Hassan Athraa Faraj Sugban |
| author_facet | Mohammed Y. Hassan Athraa Faraj Sugban |
| author_sort | Mohammed Y. Hassan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T09:15:26Z |
| format | Article |
| id | doaj.art-320f144f26bc426ba4bc9eb7b5295403 |
| institution | Directory Open Access Journal |
| issn | 2521-9154 2521-9162 |
| language | English |
| last_indexed | 2024-12-20T09:15:26Z |
| publishDate | 2018-02-01 |
| publisher | Al-Nahrain Journal for Engineering Sciences |
| record_format | Article |
| series | مجلة النهرين للعلوم الهندسية |
| spelling | doaj.art-320f144f26bc426ba4bc9eb7b52954032022-12-21T19:45:26ZengAl-Nahrain Journal for Engineering Sciencesمجلة النهرين للعلوم الهندسية2521-91542521-91622018-02-0121110.29194/NJES21010001367Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator RobotMohammed Y. Hassan0Athraa Faraj Sugban1Control and Systems Eng. Dep., University of TechnologyControl and Systems Eng. Dep., University of TechnologyThis 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.https://nahje.com/index.php/main/article/view/367Backhoe excavator robotForce-Position controlIT2FLCAnt Colony Optimization |
| spellingShingle | Mohammed Y. Hassan Athraa Faraj Sugban Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot مجلة النهرين للعلوم الهندسية Backhoe excavator robot Force-Position control IT2FLC Ant Colony Optimization |
| title | Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot |
| title_full | Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot |
| title_fullStr | Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot |
| title_full_unstemmed | Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot |
| title_short | Ant Colony Optimization Based Type-2 Fuzzy Force-Position Control for Backhoe Excavator Robot |
| title_sort | ant colony optimization based type 2 fuzzy force position control for backhoe excavator robot |
| topic | Backhoe excavator robot Force-Position control IT2FLC Ant Colony Optimization |
| url | https://nahje.com/index.php/main/article/view/367 |
| work_keys_str_mv | AT mohammedyhassan antcolonyoptimizationbasedtype2fuzzyforcepositioncontrolforbackhoeexcavatorrobot AT athraafarajsugban antcolonyoptimizationbasedtype2fuzzyforcepositioncontrolforbackhoeexcavatorrobot |