Based on the study of BP neural network and PID controller, a single neuron adaptive PSD algorithm is presented.
在对BP神经网络PID控制器系统研究的基础上，提出了单神经元的自适应PSD算法。
That the easy realization in applications of traditional PSD algorithm combine with the advantages of neuron network for model free control, is a good method for the plant having uncertainty model.
传统的PSD算法所具有的易于工程实现的特点和神经网络在非模型控制上所具有的优势，二者的结合对模型不确定性对象的控制是一个好的方法。
Furthermore, various kinds of PSD network controller were compared in this paper, and the advantage of PSD network algorithm was analyzed in theory.
并比较了现有的几种PS D网络控制器的结构特点，从理论上阐述了PS D网络算法的优势所在。
The benchmark beam of light is generated by semiconductor laser and received by light targets with PSD. Finally the measure of shaft center-line alignment is finished by optimum algorithm.
该方法以准直半导体激光光束为基准线，采用PS D光靶获取轴瓦位置二维位置信息，再由优化算法实现轴系的对中计算。
Lastly, according to the multi-temperature zone plant with time delay and strong coupling, a kind of PSD network algorithm was applicated, and the approach of algorithm is given, too.
最后，在所建立的多温区测控系统模型基础上，针对模型的大滞后、强耦合这个特点，将PS D网络解耦控制算法应用到该对象中，给出了算法的实现步骤。
Lastly, according to the multi-temperature zone plant with time delay and strong coupling, a kind of PSD network algorithm was applicated, and the approach of algorithm is given, too.
最后，在所建立的多温区测控系统模型基础上，针对模型的大滞后、强耦合这个特点，将PS D网络解耦控制算法应用到该对象中，给出了算法的实现步骤。
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