원문정보
초록
영어
In the process of the rice germination, temperature control is the key. Due to the accelerating seed germination system belongs to a complex nonlinear, large time delay and multivariable, it is difficult to establish the exact mathematical relationship model. In order to solve this problem, in this paper, we established the model based on RBF neural network, and used genetic algorithm to optimize the parameters of the neural network. In order to realize the accurate control of temperature and ensure the quality of rice sprouting, Fuzzy-PID control method can adjusts the parameters of PID and effectively improve the uniform distribution of temperature in the germinating box. The 3D graphics of temperature distribution obtained by MATLAB can show effectiveness of the method. Finally, the control strategy and system model improving the rice budding rate and evenness of emergence, are verified by experimental verification.
목차
1. Introduction
2. The Working Principle Of The Rice Sprouting
3. The Mathematical Modeling in Germination Process
3.1. Collecting and Processing of Experiment Data
3.2. Genetic Algorithm to Optimize the Design of the RBF Network
3.3. Genetic Algorithm to Optimize the Design of the RBF Network
4. The Control Of Fuzzy-PID
5. Experimental Verification
6. Conclusion
Acknowledgments
References
