Real-time adaptive tracking of DC motor speed using U-model based IMC
(2007) In Automatic Control and Computer Sciences 41(1). p.31-38- Abstract
- A novel technique, involving U-model based IMC (internal model control), is proposed for the adaptive control of nonlinear dynamic plants such as the DC-motor. The proposed scheme combines the robustness of the IMC and the ability of neural networks to identify arbitrary nonlinear functions, with the control-oriented nature of the U-model to achieve adaptive tracking of stable nonlinear plants. The proposed structure has a more general appeal than many other schemes involving polynomial NARMAX (nonlinear autoregressive moving average with exogenous inputs) model and the Hammerstein model, etc. Additionally, the control law is shown to be more simplistic in nature. The effectiveness of the proposed scheme is demonstrated with the help of... (More)
- A novel technique, involving U-model based IMC (internal model control), is proposed for the adaptive control of nonlinear dynamic plants such as the DC-motor. The proposed scheme combines the robustness of the IMC and the ability of neural networks to identify arbitrary nonlinear functions, with the control-oriented nature of the U-model to achieve adaptive tracking of stable nonlinear plants. The proposed structure has a more general appeal than many other schemes involving polynomial NARMAX (nonlinear autoregressive moving average with exogenous inputs) model and the Hammerstein model, etc. Additionally, the control law is shown to be more simplistic in nature. The effectiveness of the proposed scheme is demonstrated with the help of simulations and real-time application to the speed control of DC motor system (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1232163
- author
- Shafiq, Muhammad and Butt, Naveed LU
- publishing date
- 2007
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- adaptive control, autoregressive moving average processes, control engineering computing, DC motors, machine control, nonlinear dynamical systems, DC motor system, speed control, internal model control, nonlinear dynamic plants, neural network, nonlinear function, nonlinear autoregressive moving average model, Hammerstein model
- in
- Automatic Control and Computer Sciences
- volume
- 41
- issue
- 1
- pages
- 31 - 38
- publisher
- Allerton Press
- external identifiers
-
- scopus:34547202501
- ISSN
- 0146-4116
- DOI
- 10.3103/S0146411607010051
- language
- English
- LU publication?
- no
- id
- 07a0ab48-dad1-41f2-8052-ce403650cb84 (old id 1232163)
- alternative location
- http://www.springerlink.com/content/yu5585m0787116v0/?p=76d8f184d8c545e582f20a281ca008f1&pi=4
- date added to LUP
- 2016-04-01 15:31:05
- date last changed
- 2022-04-14 22:35:19
@article{07a0ab48-dad1-41f2-8052-ce403650cb84, abstract = {{A novel technique, involving U-model based IMC (internal model control), is proposed for the adaptive control of nonlinear dynamic plants such as the DC-motor. The proposed scheme combines the robustness of the IMC and the ability of neural networks to identify arbitrary nonlinear functions, with the control-oriented nature of the U-model to achieve adaptive tracking of stable nonlinear plants. The proposed structure has a more general appeal than many other schemes involving polynomial NARMAX (nonlinear autoregressive moving average with exogenous inputs) model and the Hammerstein model, etc. Additionally, the control law is shown to be more simplistic in nature. The effectiveness of the proposed scheme is demonstrated with the help of simulations and real-time application to the speed control of DC motor system}}, author = {{Shafiq, Muhammad and Butt, Naveed}}, issn = {{0146-4116}}, keywords = {{adaptive control; autoregressive moving average processes; control engineering computing; DC motors; machine control; nonlinear dynamical systems; DC motor system; speed control; internal model control; nonlinear dynamic plants; neural network; nonlinear function; nonlinear autoregressive moving average model; Hammerstein model}}, language = {{eng}}, number = {{1}}, pages = {{31--38}}, publisher = {{Allerton Press}}, series = {{Automatic Control and Computer Sciences}}, title = {{Real-time adaptive tracking of DC motor speed using U-model based IMC}}, url = {{http://dx.doi.org/10.3103/S0146411607010051}}, doi = {{10.3103/S0146411607010051}}, volume = {{41}}, year = {{2007}}, }