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Performance of Neural Network Based Controllers and ΔΣ-Based PID Controllers for Networked Control Systems: A Comparative Investigation

机译:基于神经网络的控制器和基于网络控制系统的PID控制器的性能:比较调查

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During the past decade, networked control systems (NCS) has emerged as a viable alternative to traditional control systems due to various advantages it offers which include a reduction in system wiring, increase of system agility etc. However, the performance of various existing controllers such as PID degrades in the networked environment due to the existence of random time-varying delay, packet-dropouts which may cause instability. The present study designs a neural network (NN) based controller for NCS and investigates its performance under random time-varying delay, packet-dropouts. The performance of this controller is compared with both the classical PID and ΔΣ-based PID controllers. The robustness of the NN based controllers in the networked environment is studied under different degree of parametric uncertainties considering an example of a DC servo mechanism. The results of the comparative investigation demonstrate that the performance of the NN based controller is superior compared to other controllers.
机译:在过去十年中,由于提供了各种优点,因此由于其提供的各种优点,因此包括减少系统接线,系统敏捷等的增加等,因此已成为传统控制系统的可行替代方案。然而,各种现有控制器的性能由于存在随机时变延迟的存在,因此可能导致不稳定性的分组丢失,因为PID在网络环境中降低。本研究设计了基于NCS的神经网络(NN)控制器,并在随机时变延迟,分组丢失下调查其性能。将该控制器的性能与基于经典PID和ΔΣ的PID控制器进行比较。在考虑DC伺服机构的示例的情况下,在不同程度的参数不确定性的不同程度下研究了基于NN的控制器的鲁棒性。比较研究结果表明,与其他控制器相比,基于NN的控制器的性能优越。

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