Delay Compensation Strategy of Networked Control System Based on Neural Network Predictive Control

The transmission delay of information in the network environment degrades the performance of networked control system, so it is necessary to compensate the delay in networked control system. This paper proposes a delay compensation strategy for networked control system based on neural network predictive control. Firstly, the BP neural network is optimized by the Cuckoo search algorithm to establish a delay prediction model to identify the transmission delay. Next, the multi-step delay prediction model is combined with the implicit generalized predictive control algorithm to solve the control increment at future sampling times. Finally, a delay compensation strategy is proposed by setting a buffer in the actuator, selecting appropriate control increments based on the delay situation to improve control accuracy and achieve delay compensation. The simulation comparison of networked gas boiler control system verifies the effectiveness of the proposed networked control system delay compensation strategy. DOI: 10.61416/ceai.v27i1.9287

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Publication Details

Journal
Journal of Control Engineering and Applied Informatics
Published
2025-03-29
DOI
https://doi.org/10.61416/ceai.v27i1.9287
Primary Topic
Advanced Sensor and Control Systems
Type
article
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article

Delay Compensation Strategy of Networked Control System Based on Neural Network Predictive Control

Zhongda Tian, Fei Tang
Journal of Control Engineering and Applied Informatics
Advanced Sensor and Control Systems
article

Delay Compensation Strategy of Networked Control System Based on Neural Network Predictive Control

Zhongda Tian, Fei Tang
article en

Abstract

The transmission delay of information in the network environment degrades the performance of networked control system, so it is necessary to compensate the delay in networked control system. This paper proposes a delay compensation strategy for networked control system based on neural network predictive control. Firstly, the BP neural network is optimized by the Cuckoo search algorithm to establish a delay prediction model to identify the transmission delay. Next, the multi-step delay prediction model is combined with the implicit generalized predictive control algorithm to solve the control increment at future sampling times. Finally, a delay compensation strategy is proposed by setting a buffer in the actuator, selecting appropriate control increments based on the delay situation to improve control accuracy and achieve delay compensation. The simulation comparison of networked gas boiler control system verifies the effectiveness of the proposed networked control system delay compensation strategy. DOI: 10.61416/ceai.v27i1.9287

Journal of Control Engineering and Applied InformaticsVol. 27(1)
Shenyang University of Technology (CN)
Openalex Percentile: Top 94%
Advanced Sensor and Control Systems
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