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| Content Provider | IET Digital Library |
|---|---|
| Author | Wu, Lan Wang, Lihua Zhang, Chunyou Shi, Hongyan |
| Abstract | The hydraulic lifting system is the key part of the crane. A sliding mode control method based on the cerebella neural network is proposed to solve the problem that the robustness of the traditional control method is poor in view of the problem of the synchronous error of the double motor in the lifting process of the crane. On the basis of the master and slave control, the outlet pressure of the hydraulic pump and the angle of the hook are simulated as the control index. Finally, the experimental study is carried out on the lifting condition. The results show that, compared with the traditional method, the proposed control strategy can effectively improve the synchronisation control precision of two motors, strong anti-interference ability and good robust performance. |
| Starting Page | 203 |
| Ending Page | 207 |
| Page Count | 5 |
| Volume Number | 2019 |
| e-ISSN | 20513305 |
| Issue Number | Issue 13, Jan (2019) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/13 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9001 |
| Journal | The Journal of Engineering |
| Publisher | The Institution of Engineering and Technology |
| Publisher Date | 2018-10-22 |
| Access Restriction | Open |
| Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
| Subject Keyword | Cerebella Neural Network Control Application to Materials Handling Control Index Crane Cranes Double Motor Dual Motor Synchronous Control Dynamic Characteristic Analysis Hydraulic Lifting System Hydraulic Pump Lifting Condition Lifting Process Master Control Material Handling Equipment Multivariable Control System Slave Control Sliding Mode Control Method Synchronisation Synchronisation Control Precision Synchronous Error Traditional Control Method Variable Structure System |
| Content Type | Text |
| Resource Type | Article |
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