| Autor: |
Xiangping Pang, Xiuran He, Kim Qian, Shousheng Xie |
| Rok vydání: |
2007 |
| Předmět: |
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| Zdroj: |
2007 IEEE International Conference on Control and Automation. |
| DOI: |
10.1109/icca.2007.4376849 |
| Popis: |
Contrast to conventional PID multi-variable decoupling control, this paper presented a new PID decoupling method based on dynamic neural network identifier (NNI) for certain turbofan engine multi-variable rotation speed control system. Each dynamic neural network was used to identify proportional coefficient kP, differential coefficient kd and integral coefficient ki, of its relevant PID decoupling controller on-line. Trans-dimensional learning as a software platform is added to the loop to improve the learning efficiency. When system unmodelled dynamics and random noise disturbance are taken into account, simulation results demonstrate the proposed decoupling strategy has strong robustness for the uncertainty and nonlinearity of aero-engine model. And it provides better disturbance rejection and adaptive capacity of the control loop than those achieved by a conventional PID decoupling controller. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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