| URN | etd-0727111-154104 | Statistics | This thesis had been viewed 934 times. Download 1 times. |
| Author | Tun-Jen Cheng | ||
| Author's Email Address | m064311@yahoo.com.tw | ||
| Department | Institute of Mechatronic Engineering | ||
| Year | 2010 | Semester | 2 |
| Degree | Master | Type of Document | Master's Thesis |
| Language | zh-TW.Big5 Chinese | Page Count | 79 |
| Title | Self Tuning Neural-PID control for electro hydraulic servo systems | ||
| Keyword | |||
| Abstract | The high performance electro-hydraulic servo systems (EHSV) need be applied to modern industry. The modern requirements of parameters variations and operation conditions variations become the new challenges for convention PID controls, which have used to be applied to electro-hydraulic servo systems. This paper is concerned with a new architecture of a self-tuning neural-PID control system and its application to control the displacement of an electro hydraulic servo system. This study proposed the three layers back propagation network to auto tuning the parameters of a conventional PID controller. The cylinder displacement of EHSV investigated by simulations, and simulation results reveal the proposed method is available for the EHSV system, and the appropriate PID control parameters can be on-line tuning by the proposed neural networks. Keywords¡Gelectro-hydraulic servo systems¡BSelf Tuning Neural-PID controls¡BPID controls¡Bposition controls |
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| Advisor Committee | |||
| Files | indicate in-campus access at one year and off-campus not accessible | ||
| Date of Defense | 2011-07-22 | Date of Submission | 2011-07-28 |