The study of PSO-RBF neural network generalized predictive control strategy in unit plant
Hui Wang, Hujun Ling, Lei Pan
Available Online September 2016.
- https://doi.org/10.2991/amitp-16.2016.14How to use a DOI?
- particle swarm optimization algorithm RBF neural network generalized predictive control generating unit
- Unit coordinated control in thermal power plants is a system which is complex,nonlinear and is difficulty to establish accurate model, So it is hard to make system gain optimum running effect with conventional control strategy. PSO-RBF neural network is used to identify the mathematical model of coordinated control system and acts as a predictive model in generalized predictive control strategy, which is to achieves predictive control with online rolling optimization and real time feedback revision. Simulation results show that it has a strong robustness when the load condition changes,or big lag affects.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Hui Wang AU - Hujun Ling AU - Lei Pan PY - 2016/09 DA - 2016/09 TI - The study of PSO-RBF neural network generalized predictive control strategy in unit plant BT - Proceedings of the 2016 4th International Conference on Advanced Materials and Information Technology Processing (AMITP 2016) PB - Atlantis Press SP - 72 EP - 76 SN - 2352-538X UR - https://doi.org/10.2991/amitp-16.2016.14 DO - https://doi.org/10.2991/amitp-16.2016.14 ID - Wang2016/09 ER -