An Intelligent System Approach to the Dynamic Hybrid Robot Control
The objective of this study was to solve the robot dynamic hybrid control problem using intelligent computational processes. In the course of problem- solving, biologically inspired models were used. This was because a robot can be seen as a physical intelligent system which interacts with the re...
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| Format: | Thesis |
| Language: | English English |
| Published: |
1996
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/9976/ http://psasir.upm.edu.my/id/eprint/9976/1/FK_1996_1_A.pdf |
| _version_ | 1848841292795084800 |
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| author | Md. Yeasin, Md. Mahmud Hasan |
| author_facet | Md. Yeasin, Md. Mahmud Hasan |
| author_sort | Md. Yeasin, Md. Mahmud Hasan |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The objective of this study was to solve the robot dynamic hybrid control
problem using intelligent computational processes. In the course of problem- solving,
biologically inspired models were used. This was because a robot can be seen as a
physical intelligent system which interacts with the real world environment by means
of its sensors and actuators. In the robot hybrid control method the neural networks,
fuzzy logics and randomization strategies were used.
To derive a complete intelligent state-of-the-art hybrid control system, several
experiments were conducted in the study. Firstly an algorithm was formulated that
can estimate the attracting basin boundary for a stable equilibrium point of a robot's kinematic nonlinear system. From this point the Artificial Neural Networks (ANN)
based solution approach was verified for the inverse kinematics solution. Secondly,
for the intelligent trajectory generation approach, the segmented tree neural networks
for each link (inverse kinematics solution) and the randomness with fuzziness
(coping the unstructured environment from the cost function) were used. A one-pass
smoothing algorithm was used to generate a practical smooth trajectory path in near
real time. Finally, for the hybrid control system the task was decomposed into
several individual intelligent control agents, where the task space was split into the
position-controlled subspaces, the force-controlled subspaces and the uncertain hyper
plane identification subspaces. The problem was considered as a blind-tracking task
by a human. |
| first_indexed | 2025-11-15T07:40:55Z |
| format | Thesis |
| id | upm-9976 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-15T07:40:55Z |
| publishDate | 1996 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-99762011-02-28T05:52:03Z http://psasir.upm.edu.my/id/eprint/9976/ An Intelligent System Approach to the Dynamic Hybrid Robot Control Md. Yeasin, Md. Mahmud Hasan The objective of this study was to solve the robot dynamic hybrid control problem using intelligent computational processes. In the course of problem- solving, biologically inspired models were used. This was because a robot can be seen as a physical intelligent system which interacts with the real world environment by means of its sensors and actuators. In the robot hybrid control method the neural networks, fuzzy logics and randomization strategies were used. To derive a complete intelligent state-of-the-art hybrid control system, several experiments were conducted in the study. Firstly an algorithm was formulated that can estimate the attracting basin boundary for a stable equilibrium point of a robot's kinematic nonlinear system. From this point the Artificial Neural Networks (ANN) based solution approach was verified for the inverse kinematics solution. Secondly, for the intelligent trajectory generation approach, the segmented tree neural networks for each link (inverse kinematics solution) and the randomness with fuzziness (coping the unstructured environment from the cost function) were used. A one-pass smoothing algorithm was used to generate a practical smooth trajectory path in near real time. Finally, for the hybrid control system the task was decomposed into several individual intelligent control agents, where the task space was split into the position-controlled subspaces, the force-controlled subspaces and the uncertain hyper plane identification subspaces. The problem was considered as a blind-tracking task by a human. 1996-04 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/9976/1/FK_1996_1_A.pdf Md. Yeasin, Md. Mahmud Hasan (1996) An Intelligent System Approach to the Dynamic Hybrid Robot Control. PhD thesis, Universiti Pertanian Malaysia. Robots - Control systems - Case studies English |
| spellingShingle | Robots - Control systems - Case studies Md. Yeasin, Md. Mahmud Hasan An Intelligent System Approach to the Dynamic Hybrid Robot Control |
| title | An Intelligent System Approach to the Dynamic Hybrid Robot Control |
| title_full | An Intelligent System Approach to the Dynamic Hybrid Robot Control |
| title_fullStr | An Intelligent System Approach to the Dynamic Hybrid Robot Control |
| title_full_unstemmed | An Intelligent System Approach to the Dynamic Hybrid Robot Control |
| title_short | An Intelligent System Approach to the Dynamic Hybrid Robot Control |
| title_sort | intelligent system approach to the dynamic hybrid robot control |
| topic | Robots - Control systems - Case studies |
| url | http://psasir.upm.edu.my/id/eprint/9976/ http://psasir.upm.edu.my/id/eprint/9976/1/FK_1996_1_A.pdf |