Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
Point-to-Point (PTP) motion control systems play an important role in industrial engineering applications such as advanced manufacturing systems, semiconductor manufacturing systems and robot systems. Until know,PID(proportionalintegral-derivative) controllers are still the most popular controller...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/19111/1/Neural-tuned_PID_Controller_05069204.pdf |
| _version_ | 1825645919408750592 |
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| author | Martono, Wahyudi Ahmad, Wali Myo, Min Htut |
| author_facet | Martono, Wahyudi Ahmad, Wali Myo, Min Htut |
| author_sort | Martono, Wahyudi |
| collection | IIUM |
| description | Point-to-Point (PTP) motion control systems play an
important role in industrial engineering applications such as advanced manufacturing systems, semiconductor manufacturing systems and robot systems. Until know,PID(proportionalintegral-derivative) controllers are still the most popular controller used in industrial control systems including PTP motion control systems due to their simplicity and also satisfactory performances. However, since the PID controller is developed based on the linear control theory, the controller gives inconsistent performance for different condition due to system nonlinearities. In order to overcome this problem, Neural-tuned PID control using model reference adaptive control (MRAC) is proposed. By using EMRAN (Extended Minimal Resource Allocation Algorithm) to train the Radial Basis Funciton (RBF)Network, the PID controller can learn, adapt and change its parameters based on the condition of the controlled-objectin real-time. The effectiveness of the proposed method is evaluated experimentally in real time using an experimental rotary positioning system. The experimental results show that the proposed system is better than classical PID controller in terms of not only positioning performance but also robustness to inertia
variations. |
| first_indexed | 2024-03-05T22:54:53Z |
| format | Proceeding Paper |
| id | oai:generic.eprints.org:19111 |
| institution | International Islamic University Malaysia |
| language | English |
| last_indexed | 2024-03-05T22:54:53Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | oai:generic.eprints.org:191112017-06-21T04:58:18Z http://irep.iium.edu.my/19111/ Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach Martono, Wahyudi Ahmad, Wali Myo, Min Htut TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery Point-to-Point (PTP) motion control systems play an important role in industrial engineering applications such as advanced manufacturing systems, semiconductor manufacturing systems and robot systems. Until know,PID(proportionalintegral-derivative) controllers are still the most popular controller used in industrial control systems including PTP motion control systems due to their simplicity and also satisfactory performances. However, since the PID controller is developed based on the linear control theory, the controller gives inconsistent performance for different condition due to system nonlinearities. In order to overcome this problem, Neural-tuned PID control using model reference adaptive control (MRAC) is proposed. By using EMRAN (Extended Minimal Resource Allocation Algorithm) to train the Radial Basis Funciton (RBF)Network, the PID controller can learn, adapt and change its parameters based on the condition of the controlled-objectin real-time. The effectiveness of the proposed method is evaluated experimentally in real time using an experimental rotary positioning system. The experimental results show that the proposed system is better than classical PID controller in terms of not only positioning performance but also robustness to inertia variations. 2009 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/19111/1/Neural-tuned_PID_Controller_05069204.pdf Martono, Wahyudi and Ahmad, Wali and Myo, Min Htut (2009) Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach. In: 5th International Colloquium on Signal Processing and Its Application, 6-8 Mar 2009, Kuala Lumpur. |
| spellingShingle | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery Martono, Wahyudi Ahmad, Wali Myo, Min Htut Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach |
| title | Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
|
| title_full | Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
|
| title_fullStr | Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
|
| title_full_unstemmed | Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
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| title_short | Neural-Tuned PID controller for Point-to-point (PTP) positioning system: model reference approach
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| title_sort | neural tuned pid controller for point to point ptp positioning system model reference approach |
| topic | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery |
| url | http://irep.iium.edu.my/19111/1/Neural-tuned_PID_Controller_05069204.pdf |
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