摘要
针对风力机和离心水泵的特点,该文设计了一种风力辅助提水机结构及其控制策略。由于该设备需要解决最大可能地利用风能和风力机与柴油机之间的功率平衡问题,因此,该系统是一个时变的2输入2输出耦合系统。根据解耦和神经网络的思想,采用2个回归神经网络(DRNN)在线调整2个PID控制器的参数,一个神经元解耦补偿器完成系统的解耦,实现了不依赖于对象模型的自适应PID解耦控制。计算机仿真结果验证了该控制策略的可行性,为进一步研究奠定了基础。
According to characteristics of wind turbine and water pump, a new scheme and its control strategy for wind power aided pumping water machine were proposed. The problems such as maximum power point tracking of wind energy and power balance between wind turbine and diesel engine need to be solved, so the system proposed is a coupling two input two output time-variable system. Based on the principle of decoupling and recurrent neural network, two Diagonal Recurrent Neural Network （DRNN） was adopted to adjust the parameters of two PID controllers online, and one nerve cell decouple compensator was adopted for decoupling the system, thus, non-model adaptive decouple PID control was implemented. Finally, the validity of the control strategy was proved via computer simulations, which can provide a foundation for further study.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2012年第4期165-168,共4页
Transactions of the Chinese Society of Agricultural Engineering
基金
西华大学重点科研基金项目(项目编号:Z1120227)
关键词
风力
泵站
耦合
PID解耦控制
回归神经网络(DRNN)
wind power
pumping plants
coupling
PID decouple control
diagonal recurrent neural network（DRNN）
