Time-delay estimator and disturbance observer based on neural network in networked control system

Xuan-Kien Dang; Van-Thu Nguyen; Xuan-Phuong Nguyen

Authors

Xuan-Kien Dang Department of Electrical and Electronic Engineering, HoChiMinh City University of Transport, Vietnam
Van-Thu Nguyen Department of Maritime Engineering, HoChiMinh City University of Transport, Vietnam
Xuan-Phuong Nguyen Department of Maritime Engineering, HoChiMinh City University of Transport, Vietnam

Keywords:

disturbance observer, networked control system, neural network, Smith predictor, time-delay estimator

Abstract

In this paper, we deal with the control problem of network induced delays and randomly varying time-delay controlled plant under the effect of disturbances and noise in networked control systems (NCS). In a time-delay NCS it becomes more challenging to attain stability when the disturbances and noise interference appear in form of a time-varying signal in the close loop of the NCS. These in turn make the conventional control methods, e.g., normal mathematical model of Smith predictor, more complicated when the aim is to meet quality requirements of the NCS. To overcome these inherent challenges, we mainly analyze the existing techniques, and then propose a novel method to efﬁciently reduce the effect of time-delays, disturbances, and noise interference for highly efﬁcient and accurate control purposes. Speciﬁcally, we introduce a joint solution of time-delay estimator and disturbance observer in which the outer loop with an adaptive Smith predictor is utilized to compensate time-delays for the whole NCS while the inner loop with disturbance observer is to eliminate the disturbances and noise interference. By using neural network identiﬁcation and the estimation method, the proposed model provides many outstanding advantages such as high adaptation, robust stability, and fast response. The simulation results generated via TrueTime Beta2.0 platform demonstrate that our design signiﬁcantly improves the performance of NCS.

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