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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Central Heating System Constrained Control with Input Delay Based on Neural Networks
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Central Heating System Constrained Control with Input Delay Based on Neural Networks

机译:基于神经网络的带输入时滞的集中供热系统约束控制。

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An output constrained control with input delay is proposed for a central heating system. Due to the delay of signal transmission and valves opening time, an input delay is considered into the system and an auxiliary system is employed to handle this issue by converting the delayed input into a delay-free one. Moreover, to ensure the output supply water temperature within a limited range, Barrier Lyapunov algorithm is involved to achieve desired control accuracy. Finally, external disturbance and model uncertainty are incorporated into the dynamic system and neural networks (NN) are trained in an online fashion for the compensation. The stability of the control system is guaranteed through rigorous Lyapunov analysis and the excellent control performance over traditional PID control is demonstrated via numerical simulation study.
机译:针对中央供暖系统,提出了具有输入延迟的输出约束控制。由于信号传输和阀门打开时间的延迟,系统考虑了输入延迟,并采用了辅助系统通过将延迟的输入转换为无延迟的输入来处理此问题。此外,为了确保输出供水温度在有限范围内,需要使用Barrier Lyapunov算法来实现所需的控制精度。最后,将外部干扰和模型不确定性纳入动态系统,并以在线方式训练神经网络(NN)进行补偿。严谨的Lyapunov分析可确保控制系统的稳定性,并通过数值模拟研究证明其优于传统PID控制。

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