Abstract
In this research, double-command control of a nonlinear chemical system is addressed. The system includes a stirred tank; two flows of liquid with different concentrations are entering the system through two valves and another flow is exiting the tank with a concentration between two input concentrations. The outlet concentration is usually regulated by the control of one of the valves and the flow rate of the second valve is fixed. The authors have already accomplished the single-command control of this system using neuro-predictive technique. Although, this problem is known as a good example for neuro-predicitve control, but this technique was found both ineffective (in terms of offering improper performance) and inefficient (in terms of needing heavy computations) when it is tried for double-command control (the control of both valves). Therefore, a fuzzy controller is designed to double-command control this system in the simulation environment. In order to avoid output chattering and frequent change of control command (leading frequent closing-opening of control valves, in practice) a damper rule is added to the fuzzy control system. A steady state control law is also derived from nonlinear mathematical model of the system to be added to transient control command whose increments are generated by fuzzy controller. The hybrid control system leads a very smooth change of control input which is suitable for real applications. The designed control systems offer lower error integral, control command change and processing time in comparison to single-command neuro-predictive controllers.
| Original language | English |
|---|---|
| Title of host publication | 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 |
| Pages | 659-664 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2008 |
| Event | 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 - Singapore, Singapore Duration: Jun 3 2008 → Jun 5 2008 |
Other
| Other | 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008 |
|---|---|
| Country | Singapore |
| City | Singapore |
| Period | 6/3/08 → 6/5/08 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Industrial and Manufacturing Engineering
Cite this
Double-command fuzzy control of a nonlinear CSTR. / Mohammadzaheri, Morteza; Chen, Lei.
2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008. 2008. p. 659-664 4582597.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Double-command fuzzy control of a nonlinear CSTR
AU - Mohammadzaheri, Morteza
AU - Chen, Lei
PY - 2008
Y1 - 2008
N2 - In this research, double-command control of a nonlinear chemical system is addressed. The system includes a stirred tank; two flows of liquid with different concentrations are entering the system through two valves and another flow is exiting the tank with a concentration between two input concentrations. The outlet concentration is usually regulated by the control of one of the valves and the flow rate of the second valve is fixed. The authors have already accomplished the single-command control of this system using neuro-predictive technique. Although, this problem is known as a good example for neuro-predicitve control, but this technique was found both ineffective (in terms of offering improper performance) and inefficient (in terms of needing heavy computations) when it is tried for double-command control (the control of both valves). Therefore, a fuzzy controller is designed to double-command control this system in the simulation environment. In order to avoid output chattering and frequent change of control command (leading frequent closing-opening of control valves, in practice) a damper rule is added to the fuzzy control system. A steady state control law is also derived from nonlinear mathematical model of the system to be added to transient control command whose increments are generated by fuzzy controller. The hybrid control system leads a very smooth change of control input which is suitable for real applications. The designed control systems offer lower error integral, control command change and processing time in comparison to single-command neuro-predictive controllers.
AB - In this research, double-command control of a nonlinear chemical system is addressed. The system includes a stirred tank; two flows of liquid with different concentrations are entering the system through two valves and another flow is exiting the tank with a concentration between two input concentrations. The outlet concentration is usually regulated by the control of one of the valves and the flow rate of the second valve is fixed. The authors have already accomplished the single-command control of this system using neuro-predictive technique. Although, this problem is known as a good example for neuro-predicitve control, but this technique was found both ineffective (in terms of offering improper performance) and inefficient (in terms of needing heavy computations) when it is tried for double-command control (the control of both valves). Therefore, a fuzzy controller is designed to double-command control this system in the simulation environment. In order to avoid output chattering and frequent change of control command (leading frequent closing-opening of control valves, in practice) a damper rule is added to the fuzzy control system. A steady state control law is also derived from nonlinear mathematical model of the system to be added to transient control command whose increments are generated by fuzzy controller. The hybrid control system leads a very smooth change of control input which is suitable for real applications. The designed control systems offer lower error integral, control command change and processing time in comparison to single-command neuro-predictive controllers.
UR - http://www.scopus.com/inward/record.url?scp=51949113430&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=51949113430&partnerID=8YFLogxK
U2 - 10.1109/ICIEA.2008.4582597
DO - 10.1109/ICIEA.2008.4582597
M3 - Conference contribution
AN - SCOPUS:51949113430
SN - 9781424417186
SP - 659
EP - 664
BT - 2008 3rd IEEE Conference on Industrial Electronics and Applications, ICIEA 2008
ER -