Name
Title | ||
|---|---|---|
Predictive control method of improved double-controller scheme based on neural networks |
Abstract | ||
|---|---|---|
This paper considers the problem of stabilizing a black-box plant with time delay using an improved double controller scheme. The PID parameters of the load controller of the double-controller scheme are obtained by a neural network controller with back propagation algorithm. Based on the adaptive algorithm of Universal Learning Network (ULN), ULN is adopted for modeling the plant and being a predictor of the control system. Simulation results prove the applicability and effectiveness of the improved double-controller scheme. ULN and the neural network controller give the double-controller scheme more representing abilities and robust ability. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11760023_140 | ISNN (2) |
Keywords | Field | DocType |
improved double controller scheme,propagation algorithm,load controller,pid parameter,double-controller scheme,black-box plant,predictive control method,improved double-controller scheme,neural network controller,universal learning network,adaptive algorithm,neural network,control system,predictive control | Computer science,Control theory,Model predictive control,Artificial intelligence,Control system,Artificial neural network,Black box (phreaking),Control theory,PID controller,Algorithm,Adaptive algorithm,Backpropagation,Machine learning | Conference |
Volume | ISSN | ISBN |
3972 | 0302-9743 | 3-540-34437-3 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
2 | ||