Implementation of neural-network-based inverse-model control strategies on an exothermic reactor
In recent years there has been a significant increase in the number of control system techniques that are based on nonlinear concepts. One such method is the nonlinear inverse-model based control strategy. This method is however highly dependent on the availability of the inverse of the system model...
| id |
um-7081 |
|---|---|
| recordtype |
eprints |
| spelling |
um-70812013-07-10T07:30:24Z Implementation of neural-network-based inverse-model control strategies on an exothermic reactor Hussain, Mohamed Azlan Kittisupakorn, Paisan Daosu, Wachira TA Engineering (General). Civil engineering (General) TP Chemical technology In recent years there has been a significant increase in the number of control system techniques that are based on nonlinear concepts. One such method is the nonlinear inverse-model based control strategy. This method is however highly dependent on the availability of the inverse of the system model under control, which are normally difficult to obtain analytically for nonlinear systems. Since neural networks have the ability to model many nonlinear systems including their inverses, their use in this control scheme is highly promising. In this work, we investigate the use of these neural-network-based inverse model control strategy to control an exothermic reactor. The use of the specialised method of training the inverse neural network model is demonstrated. The utilization of two different inverse-model schemes namely the direct inverse control and the internal-model control methods are shown for both set point and disturbance rejection cases. The overall results for set point tracking are good in both control strategies but the direct inverse control method had limitations when dealing with disturbances. Other important aspects relating to the use of neural networks for identification and controls are also discussed in this paper. Science Asia 2001 Article PeerReviewed application/pdf http://eprints.um.edu.my/7081/1/Implementation_of_neural%2Dnetwork%2Dbased_inverse%2Dmodel_control_strategies_on_an_exothermic_reactor.pdf https://www.thaiscience.info/journals/Article/Implementation%20of%20neural-network-based%20inverse-model%20control%20strategies%20on%20an%20exothermic%20reactor.pdf Hussain, Mohamed Azlan; Kittisupakorn, Paisan; Daosu, Wachira (2001) Implementation of neural-network-based inverse-model control strategies on an exothermic reactor. Science Asia <http://eprints.um.edu.my/view/publication/Science_Asia.html>, 27. pp. 41-50. http://eprints.um.edu.my/7081/ |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
University Malaya |
| building |
UM Research Repository |
| collection |
Online Access |
| topic |
TA Engineering (General). Civil engineering (General) TP Chemical technology |
| spellingShingle |
TA Engineering (General). Civil engineering (General) TP Chemical technology Hussain, Mohamed Azlan Kittisupakorn, Paisan Daosu, Wachira Implementation of neural-network-based inverse-model control strategies on an exothermic reactor |
| description |
In recent years there has been a significant increase in the number of control system techniques that are based on nonlinear concepts. One such method is the nonlinear inverse-model based control strategy. This method is however highly dependent on the availability of the inverse of the system model under control, which are normally difficult to obtain analytically for nonlinear systems. Since neural networks have the ability to model many nonlinear systems including their inverses, their use in this control scheme is highly promising. In this work, we investigate the use of these neural-network-based inverse model control strategy to control an exothermic reactor. The use of the specialised method of training the inverse neural network model is demonstrated. The utilization of two different inverse-model schemes namely the direct inverse control and the internal-model control methods are shown for both set point and disturbance rejection cases. The overall results for set point tracking are good in both control strategies but the direct inverse control method had limitations when dealing with disturbances. Other important aspects relating to the use of neural networks for identification and controls are also discussed in this paper. |
| format |
Article |
| author |
Hussain, Mohamed Azlan Kittisupakorn, Paisan Daosu, Wachira |
| author_facet |
Hussain, Mohamed Azlan Kittisupakorn, Paisan Daosu, Wachira |
| author_sort |
Hussain, Mohamed Azlan |
| title |
Implementation of neural-network-based inverse-model control strategies on an exothermic reactor |
| title_short |
Implementation of neural-network-based inverse-model control strategies on an exothermic reactor |
| title_full |
Implementation of neural-network-based inverse-model control strategies on an exothermic reactor |
| title_fullStr |
Implementation of neural-network-based inverse-model control strategies on an exothermic reactor |
| title_full_unstemmed |
Implementation of neural-network-based inverse-model control strategies on an exothermic reactor |
| title_sort |
implementation of neural-network-based inverse-model control strategies on an exothermic reactor |
| publisher |
Science Asia |
| publishDate |
2001 |
| url |
https://www.thaiscience.info/journals/Article/Implementation%20of%20neural-network-based%20inverse-model%20control%20strategies%20on%20an%20exothermic%20reactor.pdf https://www.thaiscience.info/journals/Article/Implementation%20of%20neural-network-based%20inverse-model%20control%20strategies%20on%20an%20exothermic%20reactor.pdf http://eprints.um.edu.my/7081/1/Implementation_of_neural%2Dnetwork%2Dbased_inverse%2Dmodel_control_strategies_on_an_exothermic_reactor.pdf |
| first_indexed |
2018-09-06T05:23:56Z |
| last_indexed |
2018-09-06T05:23:56Z |
| _version_ |
1610834443151343616 |