Title | ||
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A Multiple Models Approach for Adaptive Predictive Control of Networked Control Systems |
Abstract | ||
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A real-time, self-learning, multiple models adaptive predictive control algorithm is proposed for Networked Control Systems(NCS), which can deal with different distributions of time delay introduced by a communication network or a field bus. The algorithm keeps updating the dynamic models in a model bank, and uses an adaptive model to track the parameter changes of NCS. In the mean time, it uses another adaptive model to ensure the stability of the overall NCS. The convergence analysis shows that the algorithm will finally switch to and stop at a stable, adaptive model. |
Year | DOI | Venue |
---|---|---|
2007 | 10.1109/ICNC.2007.76 | ICNC |
Keywords | Field | DocType |
dynamic model,predictive control algorithm,model bank,adaptive model,overall ncs,multiple model,networked control systems,multiple models approach,time delay,mean time,adaptive predictive control,communication network,adaptive control,real time,stability,networked control system,predictive control | Convergence (routing),Telecommunications network,Computer science,Control theory,Networked control system,Model predictive control,Dynamic models,Adaptive control,Control system,Multiple Models | Conference |
Volume | ISSN | ISBN |
2 | 2157-9555 | 0-7695-2875-9 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Chunmao Li | 1 | 0 | 0.34 |
Jian Xiao | 2 | 379 | 34.37 |
Lili Chu | 3 | 0 | 0.34 |
Junhua Liu | 4 | 1 | 3.05 |