基于Smith补偿与神经网络的网络控制系统PD控制

为减小网络时延给系统控制性能带来的负面影响，把传输网络以及被控对象看作是一个时变的被控系统，用Smith补偿器对时延进行补偿，并用遗忘因子递推最小二乘法对Smith补偿器中的参数进行估计，初步减小网络传输时延给系统带来的影响。将小脑模型控制器与PD控制相结合，组成复合控制器，进一步减小由时延预估误差带给系统的控制偏差，优化系统控制效果。最后，对该控制方法进行仿真实验，结果表明该方法能有效改善系统的控制性能。

PD control of networked control system based on Smith compensation and neural network

In order to compensate the time delay, the plant and network are regarded as one time varying system, which is predicted by least square estimation. Based on this, a Smith compensator is used to compensate the time delay of the system. The complex controller including a cerebellar model articulation controller of neural networks and a PD controller is applied to the system to weaken the prediction error further, while the control performance can be improved. The simulation results show the method can improve the control performance.