Title :
Research on Multivariable Time Delay System Multi-step Predictive Dynamic Modeling
Author :
Shi, Buhai ; Zhu, Xuefeng
Author_Institution :
South China Univ. of Technol., Gangzhou
fDate :
May 30 2007-June 1 2007
Abstract :
This paper introduces a dynamic modeling method of multi-step predictive neural network in the large time delay system, and discusses the algorithm and structure of neural network and dynamic response characteristics of the large time delay system in detail. Especially, based on single variable time delay system modeling framework, a new algorithm is presented to implement the neural network multi-step predictive modeling of multivariable large time delay system. According to the data of the waterworks coagulating sedimentation time delay system, the simulation of the multivariable multi-step predictive modeling shows that these results are effective.
Keywords :
coagulation; delay systems; delays; multivariable control systems; neurocontrollers; predictive control; purification; sedimentation; simulation; water treatment; multistep predictive dynamic modeling; multivariable time delay system; neural network; simulation; waterworks coagulating sedimentation; Artificial neural networks; Automatic control; Automation; Convergence; Delay effects; Fuzzy control; Fuzzy neural networks; Neural networks; Predictive models; Three-term control; LMBP; coagulating sedimentation system; dynamic modeling; multi-step predictive; time delay system;
Conference_Titel :
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4244-0818-4
Electronic_ISBN :
978-1-4244-0818-4
DOI :
10.1109/ICCA.2007.4376720
