| URN |
etd-0726116-113710 |
Statistics |
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|
| Author |
LIAO-ZHAN MIN |
| Author's Email Address |
james810215@gmail.com |
| Department |
Institute Of Mechanical Engineering |
| Year |
2015 |
Semester |
2 |
| Degree |
Master |
Type of Document |
Master's Thesis |
| Language |
zh-TW.Big5 Chinese |
Page Count |
54 |
| Title |
The neural networks and PID hybrid controller applied to temperature control for air conditioning systems |
| Keyword |
Hybrid Control
Neural network
Variable Refrigerant Volume
Inverter Air Conditioning System
Inverter Air Conditioning System
Variable Refrigerant Volume
Neural network
Hybrid Control
|
| Abstract |
The air conditioning systems apply variable refrigerant flow (VRF) techniques for Energy saving, which also called VRF air conditioning systems. The VRF air conditioning systems can change the refrigerant flow by changing the compressor speed, and usually applied to home and small office space. The modern VRF air conditioning systems applied variable speed compressors with nonlinear characteristics, and the varied room space and refrigerating load requirements lead the PID control becomes insufficient for modern VRF air conditioning systems. This study utilizes the neural network and PID hybrid controls applied to VRF air conditioner system for room temperature control, which can enhance the adaptability and saving energy. The simulation results reveal that the proposed control system can enhance the adaptability and be available with better energy saving performance than PID control. |
| Advisor Committee |
Chu-Ming Huei - advisor
HUANG,JHENG-GUANG - co-chair
YANG,JHIH-SHENG - co-chair
|
| Files |
indicate in-campus access at 3 years and off-campus access at 3 years |
| Date of Defense |
2016-07-08 |
Date of Submission |
2016-07-26 |
