Abstract
In this paper, online optimization problem of model predictive control (MPC) of time-delayed system with restraints is described as an quadratic programming (QP) problem with restraints and a dual neural network is used to solve this problem. This neurodynamical optimization method exerts the advanteages of neural network that neural network can solve problems in parallelly and distributedly, and has fast optimization speed; and this method can be used to solve all kinds of complicated optimization problems with restraints. Experiment study results show that the proposed MPC method has good optimization precision and optimization speed, and this neurodynamical optimization method improves the online optimization capability of MPC. The proposed MPC method based on neurodynamical optimization extends the application fields of MPC.
| Translated title of the contribution | Model predictive control of time-delayed restraint system based on neurodynamical optimization |
|---|---|
| Original language | Chinese (Simplified) |
| Pages (from-to) | 961-966 |
| Journal | 仪器仪表学报 |
| Volume | 34 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - May 2013 |
| Externally published | Yes |
Research Keywords
- 时滞系统
- 神经动态优化
- 模型预测控制
- Time-delayed system
- Neurodynamical optimization
- Model predictive control (MPC)
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