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

Chathura Wanigasekara, D. Almakhles, A. Swain, S. Nguang, Umashankar Subramaniyan, Sanjeevikumar Padmanaban
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引用次数: 4

Abstract

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.
神经网络控制器与ΔΣ-Based PID控制器在网络控制系统中的性能比较研究
在过去的十年中,网络控制系统(NCS)已经成为传统控制系统的可行替代方案,因为它提供了各种优势,包括减少系统布线,增加系统敏捷性等。然而,在网络环境中,由于随机时变延迟和丢包的存在,现有的各种控制器(如PID)的性能会下降,这可能会导致不稳定。本文设计了一种基于神经网络的NCS控制器,并对其在随机时变延迟、丢包等情况下的性能进行了研究。将该控制器的性能与经典PID和ΔΣ-based PID控制器进行了比较。以直流伺服机构为例,研究了网络环境下不同参数不确定程度下基于神经网络的控制器的鲁棒性。对比研究结果表明,基于神经网络的控制器性能优于其他控制器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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