PID Neural Network Decoupling Control of Multi-variable System and its Application
- https://doi.org/10.2991/icimm-16.2016.54How to use a DOI?
- MPIDNN; Decoupling Control; Multi-variable; Simulation
In this thesis, multi-output PID neural network (MPIDNN) is proposed based on the research on single-output PID and it is simulated. MPIDNN is also proposed for the characteristics of coupling system which is difficult to control in industrial process. The results of the simulation show that the control algorithm has the function of online learning to adjust parameters. For multi-input and multi-output system, by using the MPIDNN decoupling control method, there is no need to get the exact model of object. It can offset the effects of the internal model or other disturbance and achieve better control effect.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - DongJiang Yu AU - WeiZhi Long AU - JiaBing He PY - 2016/11 DA - 2016/11 TI - PID Neural Network Decoupling Control of Multi-variable System and its Application BT - Proceedings of the 6th International Conference on Information Engineering for Mechanics and Materials PB - Atlantis Press SP - 288 EP - 293 SN - 2352-5401 UR - https://doi.org/10.2991/icimm-16.2016.54 DO - https://doi.org/10.2991/icimm-16.2016.54 ID - Yu2016/11 ER -