PID Neural Network Adaptive Predictive Control for Long Time Delay System

2013 ◽  
pp. 283-292 ◽  
Author(s):  
Yang Zhi-gang ◽  
Qian Jun-lei
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Predictive Control ◽  
Delay System ◽  
Time Delay System ◽  
Long Time ◽  
Adaptive Predictive Control ◽  
Pid Neural Network

scholarly journals Control Method Based On Long Time-delay System

2020 ◽  
Vol 1605 ◽  
pp. 012027
Author(s):  
Ling Huang ◽  
Rui Tang ◽  
Pei Xia ◽  
Cheng Tan
Keyword(s):  
Time Delay ◽  
Control Method ◽  
Delay System ◽  
Time Delay System ◽  
Long Time

A Time-Delay Prediction Control Method Based on Immune Optimization

2011 ◽  
Vol 317-319 ◽  
pp. 1250-1254
Author(s):  
Xue Song Xu ◽  
Xing Bao Liu
Keyword(s):  
Time Delay ◽  
Predictive Control ◽  
Control Method ◽  
Clonal Selection ◽  
Delay System ◽  
Time Delay System ◽  
Immune Optimization ◽  
Process System ◽  
Prediction Control ◽  
Delay Prediction

A time-delay predictive control algorithm based on immune computational intelligences is proposed in this paper. The predictive control parameter was optimized through immune clonal selection. Which avoids calculate Diophantine equation and inverse matrix, reduces the input dimensions of the nonlinear map. Simulations were conducted on the time-delay system, non-minimum phase of the process system, divergent system illustrate that this approach is a feasibility and effectiveness way and demonstrate its rapid responds, small overshoot and high adaptability for time delay system.

scholarly journals The Research of Improved Active Disturbance Rejection Control Algorithm for Particleboard Glue System Based on Neural Network State Observer

Algorithms ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 259
Author(s):  
Peiyu Wang ◽  
Chunrui Zhang ◽  
Liangkuan Zhu ◽  
Chengcheng Wang
Keyword(s):  
Neural Network ◽  
Time Delay ◽  
Disturbance Rejection ◽  
Sliding Mode ◽  
Control Object ◽  
State Observer ◽  
Delay System ◽  
Time Delay System ◽  
Network State ◽  
Active Disturbance Rejection

For achieving high-performance control for a particleboard glue mixing and dosing control system, which is a time-delay system in low frequency working conditions, an improved active disturbance rejection controller is proposed. In order to reduce overshoot caused by a given large change between the actual output and expected value of the control object, a tracking differentiator (TD) is used to arrange the appropriate excesses. Through the first-order approximation of the time-delay link, the time-delay system is transformed into an output feedback problem with unknown function. Using the neural network state observer (NNSO), a sliding mode control law is used to achieve the accurate and fast tracking of the output signal. Finally, the numerical simulation results verify the effectiveness and feasibility of the proposed method.

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