Optimal disturbance rejection control approach based on a compound neural network prediction method |
| |
| Affiliation: | 1. School of Automation, Southeast University, Nanjing 210096, PR China;2. Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, PR China;3. School of Hydraulic, Energy and Power Engineering, Yangzhou University, Yangzhou 225127, PR China;1. Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran;2. Department of Electrical Power Engineering, Tishreen University, Lattakia, Syria;1. Iran University of Science and Technology, Narmak, Tehran 1684613114, Iran;2. Department of Engineering, University of Zanjan, University Blvd., 4537138791 Zanjan, Iran |
| |
| Abstract: | A new optimal disturbance rejection control method is proposed for the system with disturbances via a compound neural network prediction approach in this paper. The disturbances caused by external disturbances and model mismatches can be estimated by a disturbance observer, and the estimation of disturbances is introduced into the neural network predictive model to make the predictive output more accurate. Then based on the new compound neural network predictive model, a controller, which ensures both optimal performance by the receding horizon optimization and strong disturbance rejection ability, is obtained. The proposed scheme is applied to control the temperature of a simplified jacketed stirred tank heater (JSTH). Simulation results demonstrate the effectiveness of the proposed control method. |
| |
| Keywords: | Compound neural network prediction Optimal disturbance rejection Model mismatches Disturbance observer Receding horizon optimization Temperature control |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
