RBF网络自整定PID控制在网络化控制系统中的应用

Application of RBF neural network self-tuning PID control in network control system

文章针对网络化控制系统普遍存在的时延问题,介绍了一种基于径向基函数神经网络自整定PID的控制策略。在Matlab/Simulink环境下搭建了基于TrueTime工具箱的网络控制系统的仿真平台。仿真结果表明:与常规PID控制相比,神经网络自整定PID控制算法可有效地提高系统的鲁棒性和自适应性,且此方法易于实现,便于工程应用。

Aiming at the universal problem of time delay in network control system（NCS）, a control strategy based on radial basis function（RBF） neural network self-tuning PID is provided. A simula- tion model of NCS is established under the environment of TrueTime toolbox based Matlab/Simulink. The simulation results indicate that compared with the traditional PID control, the RBF neural net- work self-tuning PID control can effectively improve the robustness and self-adaptability of the system, and can be applied to real projects easily.