Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints
In this paper, an adaptive neural network control method is described to stabilize a continuous stirred tank reactor (CSTR) subject to unknown time-varying delays and full state constraints. The unknown time delay and state constraints problem of the concentration in the reactor seriously affect the...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/9948044 |
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| _version_ | 1832548887719575552 |
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| author | Dongjuan Li Dongxing Wang Ying Gao |
| author_facet | Dongjuan Li Dongxing Wang Ying Gao |
| author_sort | Dongjuan Li |
| collection | DOAJ |
| description | In this paper, an adaptive neural network control method is described to stabilize a continuous stirred tank reactor (CSTR) subject to unknown time-varying delays and full state constraints. The unknown time delay and state constraints problem of the concentration in the reactor seriously affect the input-output ratio and stability of the entire system. Therefore, the design difficulty of this control scheme is how to debar the effect of time delay in CSTR systems. To deal with time-varying delays, Lyapunov–Krasovskii functionals (LKFs) are utilized in the adaptive controller design. The convergence of the tracking error to a small compact set without violating the constraints can be identified by the time-varying logarithm barrier Lyapunov function (LBLF). Finally, the simulation results on CSTR are shown to reveal the validity of the developed control strategy. |
| format | Article |
| id | doaj-art-64be7cfe5baf4ff6a8d054206d17a385 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-64be7cfe5baf4ff6a8d054206d17a3852025-02-03T06:12:50ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/99480449948044Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State ConstraintsDongjuan Li0Dongxing Wang1Ying Gao2School of Chemical and Environmental Engineering, Liaoning University of Technology, Jinzhou 121001, Liaoning, ChinaSchool of Chemical and Environmental Engineering, Liaoning University of Technology, Jinzhou 121001, Liaoning, ChinaSchool of Mathematics and Computational Sciences, Tangshan Normal University, Tangshan 63000, Hebei, ChinaIn this paper, an adaptive neural network control method is described to stabilize a continuous stirred tank reactor (CSTR) subject to unknown time-varying delays and full state constraints. The unknown time delay and state constraints problem of the concentration in the reactor seriously affect the input-output ratio and stability of the entire system. Therefore, the design difficulty of this control scheme is how to debar the effect of time delay in CSTR systems. To deal with time-varying delays, Lyapunov–Krasovskii functionals (LKFs) are utilized in the adaptive controller design. The convergence of the tracking error to a small compact set without violating the constraints can be identified by the time-varying logarithm barrier Lyapunov function (LBLF). Finally, the simulation results on CSTR are shown to reveal the validity of the developed control strategy.http://dx.doi.org/10.1155/2021/9948044 |
| spellingShingle | Dongjuan Li Dongxing Wang Ying Gao Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints Complexity |
| title | Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints |
| title_full | Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints |
| title_fullStr | Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints |
| title_full_unstemmed | Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints |
| title_short | Adaptive Neural Control and Modeling for Continuous Stirred Tank Reactor with Delays and Full State Constraints |
| title_sort | adaptive neural control and modeling for continuous stirred tank reactor with delays and full state constraints |
| url | http://dx.doi.org/10.1155/2021/9948044 |
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