The New Variable-period Sampling Scheme for Networked Control Systems with Random Time Delay Based on BP Neural Network Prediction

2006 ◽  
Author(s):  
Liu Jiangang ◽  
Liu Biyu ◽  
Zhang Ruifang ◽  
Li Meilan
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Control Systems ◽  
Bp Neural Network ◽  
Networked Control Systems ◽  
Networked Control ◽  
Random Time ◽  
Sampling Scheme ◽  
Neural Network Prediction ◽  
Network Prediction

Research on Networked Control Systems Based on Adaptive Predictive Control

2013 ◽  
Vol 441 ◽  
pp. 833-836
Author(s):  
Zai Ping Chen ◽  
Xue Wang
Keyword(s):  
Time Delay ◽  
Control Systems ◽  
Predictive Control ◽  
Control Strategy ◽  
Networked Control Systems ◽  
Networked Control ◽  
Random Time ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Adaptive Predictive Control

According to the random time-delay exist in sensor-controller channel and controller-actuator channel in networked control systems, an adaptive predictive control strategy was proposed. In this control strategy, an improved generalized predictive control algorithm is adopted to compensate the networked random time-delay. In addition, using the recursive least squares with a variable forgetting factor algorithm to indentify the model parameters of controlled object on-line, through the way, it could adjust the systems with unknown parameters adaptively. Simulation results show that the adaptive predictive control proposed could solve random time-delay of networked control systems effectively.

Period-Varying Sampling Scheme for Networked Control Systems

2011 ◽  
Vol 279 ◽  
pp. 445-450
Author(s):  
Yan Shen ◽  
Bing Guo
Keyword(s):  
Control Systems ◽  
Bp Neural Network ◽  
Network Performance ◽  
Networked Control Systems ◽  
Sampling Period ◽  
Data Packet ◽  
Networked Control ◽  
Sampling Scheme ◽  
Network Resources ◽  
Current Sampling

In the networked control systems, control performance and network performance are closely related to the sampling period influenced by the network-induced delay. So in order to improve the network performance by adjusting the current sampling period, a period-vary sampling scheme is proposed based on an adjuster for the sampling period designed. In this scheme, the adjuster consists of a monitor, which acquires network resources utilization and the executive time of data packet, and a predictor, which uses BP neural network to predict the next sampling period by utilizing network resources utilization and data packet executive time. The simulation results show that the proposed scheme can alleviate the influence of time delay and improve the performance of the networked control systems.

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