Computer Engineering and Applications ›› 2016, Vol. 52 ›› Issue (16): 216-220.

### Wavelet neural network generalized predictive control for quadruple-tank system

SONG Qingkun1, YU Shanyu2, HAN Xiao1

1. 1.School of Automation, Harbin University of Science and Technology, Harbin 150080, China
2.Shenzhen Clou Electronics Corporation Limited, Shenzhen, Guangdong 518057, China
• Online:2016-08-15 Published:2016-08-12

### 四容水箱的小波神经网络广义预测控制

1. 1.哈尔滨理工大学 自动化学院，哈尔滨 150080
2.深圳科陆电子科技股份有限公司，广东 深圳 518057

Abstract: Considering the characteristic of the quadruple-tanks, such as multiple variables, great time-delay, misalignment and coupling, the author applies the wavelet neural network generalized predictive control（WNNGPC）. Predictive model of the control system can be obtained through recognizing the system controlled object based on the good function approximation of the wavelet neural network. And with the combination of the good control performance of the generalized predictive control, the quadruple-tanks system can achieve stability control. During the reorganization of the system, the author applies the optimal BP neural network. This algorithm can correct weights and thresholds of the network quickly, and make the prediction output approaching the desired output smoothly. On solving the coupled problem of system, the author designs a fuzzy feed forward compensation decoupling by using the universal approximation of fuzzy control. Use the WNNGPC based on fuzzy compensation decoupling to do the experiments of the quadruple-tanks, and analyze the results of experiments. Through the experiments and analysis, it can be indicated that the control strategy achieves good control effect of the quadruple-tanks.