Name
Abstract | ||
|---|---|---|
A Robust-Intelligent controller based on sliding mode control theory and neural network is presented to reduce the bullwhip effect in supply chain. A state space model used to design and evaluate the performance of the proposed controller. The neural network control strategy is studied to overcome the “chattering” of the sliding mode controller. The numerical simulations are curried out to check the effectiveness of proposed robust-intelligent controller. The obtained results demonstrate that the proposed controller can effectively suppress the bullwhip effect. Furthermore it is shown that the chattering of sliding mode controller is smoothed when it is integrated with a neural network control strategy. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IS.2010.5548389 | IEEE Conf. of Intelligent Systems |
Keywords | Field | DocType |
control nonlinearities,neurocontrollers,numerical analysis,robust control,state-space methods,supply chains,variable structure systems,bullwhip effect attenuation,chattering,neural network control strategy,numerical simulations,robust intelligent controller,sliding mode control theory,state space model,supply chain,RBF network,bullwhip effect,chattering reduction,sliding mode control,supply chain | Control theory,Control theory,Computer science,State-space representation,Bullwhip effect,Robustness (computer science),Supply chain,Artificial neural network,Robust control,Sliding mode control | Conference |
ISBN | Citations | PageRank |
978-1-4244-5164-7 | 1 | 0.38 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mahdi Ghane | 1 | 1 | 0.38 |
| Mohammad Zarvandi | 2 | 1 | 0.38 |
| Mohammad Reza Yousefi | 3 | 1 | 0.38 |