Neural networks in virtual reference tuning
作者： Alicia Esparza , Antonio Sala , Pedro Albertos
DOI: 10.1016/J.ENGAPPAI.2011.04.003
关键词:
摘要: Abstract This paper discusses the application of virtual reference tuning (VRT) techniques to tune neural controllers from batch input–output data, by particularising nonlinear VRT and suitably computing gradients backpropagating in time. The flexibility gradient computation with networks also allows alternative block diagrams extra inputs be considered. approach a closed-loop setup is compared linear VRFT one simulated crane example.
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sci-hub.se 参考文章(52)
G. P. Liu, Nonlinear Identification and Control ,(2001)
M. Gevers, Towards a Joint Design of Identification and Control Essays on Control. pp. 111- 151 ,(1993) , 10.1007/978-1-4612-0313-1_5
Ieroham Baruch, Direct and Indirect Adaptive Neural Control of Nonlinear Systems Hybrid Intelligent Systems. pp. 95- 114 ,(2007) , 10.1007/978-3-540-37421-3_6
Robert Tibshirani, Trevor Hastie, Jerome H. Friedman, The Elements of Statistical Learning ,(2001)
Alireza Karimi, Klaske van Heusden, Dominique Bonvin, Non-iterative data-driven controller tuning using the correlation approach european control conference. pp. 5189- 5195 ,(2007) , 10.23919/ECC.2007.7068802
Christopher M. Bishop, Neural networks for pattern recognition ,(1995)
Larry R. Medsker, Hybrid Intelligent Systems ,(1995)
H. L. Trentelman, Jan C. Willems, Essays on control : perspectives in the theory and its applications Birkhäuser. ,(1993)
Neural networks for control american control conference. ,vol. 3, pp. 1642- 1656 ,(1999) , 10.1109/ACC.1999.786109
G.P. Liu, Nonlinear Identification and Control: A Neural Network Approach ,(2012)