Finally, we present a new control scheme of air pressure and flow and build PID decoupling control arithmetic based DRNN of air control system.
最后，提出了新的气源压力、流量系统控制方案，建立了对气源压缩空气压力、流量系统的基于神经网络整定的PID解耦控制算法。
After the success in decoupling, single neural cell self-adapting PID is adopted to control nonlinear object. The simulation results show that the control strategy gets better effects.
当解耦器训练结束后，对于非线性对象采用单神经元自适应PID来进行控制，仿真结果表明，此控制方案效果较好。
Adopting new type diagonal regression neural network to identify the system model, the parameters of PID controller have been set, and the multi -variable decoupling control being realized.
采用新型对角回归神经网络来辩识系统模型，可对PID控制器参数进行整定，实现多变量解耦控制。
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