节点文献
基于MNN神经网络的液压系统油温的PWM自学习控制
PWM Self-Learniug Coutrol for the Oil Temperature in Hydraulic System Based on Memory Neural Network
【摘要】 基于PWM脉冲宽度调节原理,提出开关式冷却系统的PWM控制策略,降低了冷却系统成本,同时提高了系统可靠性。利用MNN动态回归网络提出滞后复杂系统的自学习控制算法,用于液压系统油温的高精度控制,取得令人满意的控制效果。
【Abstract】 Based on pulse width modulation (PWM) theory, a PWM controlled on-off cooling system is proposed in this paper,the cost of the cooling system is decreased and the reliability is increased. Using memory neural network (MNN),this paper describes a neural network self-learning control algorithm for the control of complex system with time-delay, and the control algorithm is used in the oil temperature control in hydraulic system, the experimental result is satisfactory, the oil temperature is controlled within 50±0. 5℃.
【关键词】 MNN神经网络;
自学习控制;
温度控制;
脉宽调制;
【Key words】 memory neural network (MNN ) selflearning control algorithm temperature control;
【Key words】 memory neural network (MNN ) selflearning control algorithm temperature control;
【基金】 国家博士点基金!9214515
- 【文献出处】 中国机械工程 ,China Mechanical Engineering(中国机械工程) , 编辑部邮箱 ,1998年07期
- 【分类号】TH137
- 【被引频次】22
- 【下载频次】108