The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control
Abstract
This paper investigates the multirate networked industrial process control problem in double-layer architecture. First, the output tracking problem for sampled-data nonlinear plant at device layer with sampling period T(d) is investigated using adaptive neural network (NN) control, and it is shown that the outputs of subsystems at device layer can track the decomposed setpoints. Then, the outputs and inputs of the device layer subsystems are sampled with sampling period T(u) at operation layer to form the index prediction, which is used to predict the overall performance index at lower frequency. Radial basis function NN is utilized as the prediction function due to its approximation ability. Then, considering the dynamics of the overall closed-loop system, nonlinear model predictive control method is proposed to guarantee the system stability and compensate the network-induced delays and packet dropouts. Finally, a continuous stirred tank reactor system is given in the simulation part to demonstrate the effectiveness of the proposed method.
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Citations
Cites
Constrained model predictive control: Stability and optimality
Mayne, D. Q., Rawlings, J. B., Rao, C. V., & Scokaert, P. O. M. (2000) · Automatica · doi:10.1016/s0005-1098(99)00214-9 · Cited by 8,736
Cited by
Lei, Y., Jia, F., Lin, J., Xing, S., & Ding, S. X. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2519325 · Cited by 1,191
Observer-based adaptive sliding mode control for nonlinear Markovian jump systems
Li, H., Shi, P., Yao, D., & Wu, L. (2016) · Automatica · doi:10.1016/j.automatica.2015.11.007 · Cited by 533
Qiu, J., Ding, S. X., Gao, H., & Yin, S. (2016) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2015.2457934 · Cited by 382
Self-citationAdaptive Neural Control of Stochastic Nonlinear Time-Delay Systems With Multiple Constraints
Wang, T., Qiu, J., & Gao, H. (2017) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2016.2562511 · Cited by 170
Self-citationAdaptive Neural Control of MIMO Nonstrict-Feedback Nonlinear Systems With Time Delay
Zhao, X., Yang, H., Karimi, H. R., & Zhu, Y. (2016) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2015.2441292 · Cited by 130
Metadata
- Authors
- Wang, T., Gao, H., & Qiu, J.
- Venue
- IEEE Transactions on Neural Networks and Learning Systems
- Published
- 2016-02
- Volume
- 27
- Issue
- 2
- Pages
- 416-425
- ISSN
- 2162-237X (ISSN-L)
- 2162-2388
- OpenAlex
- W1977230515
- Cited by
- 636
- References
- 1
- FWCI
- 112.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, T., Gao, H., & Qiu, J. (2016). A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2015.2411671
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