Neural networks in control systems
作者： K.S. Narendra , S. Mukhopadhyay
关键词: Activation function 、 Adaptive control 、 Artificial neural network 、 Control engineering 、 Radial basis function network 、 Control theory 、 Time delay neural network 、 Nonlinear system 、 Intelligent control 、 Computer science 、 Radial basis function 、 Control system
摘要: Some of the problems that arise in control nonlinear systems presence uncertainty are considered. Multilayer neural networks and radial basis function used design identifiers controllers, gradient methods to adjust their parameters. For a restricted class systems, it is shown globally stable adaptive controllers can be determined. Simulation results presented demonstrate for effective complex systems. >
sci-hub.se 参考文章(5)
Eduardo D. Sontag, Mathematical Control Theory: Deterministic Finite Dimensional Systems ,(1990)
Ronald J. Williams, David Zipser, A learning algorithm for continually running fully recurrent neural networks Neural Computation. ,vol. 1, pp. 270- 280 ,(1989) , 10.1162/NECO.1989.1.2.270
K.S. Narendra, K. Parthasarathy, Identification and control of dynamical systems using neural networks IEEE Transactions on Neural Networks. ,vol. 1, pp. 4- 27 ,(1990) , 10.1109/72.80202
K.S. Narendra, K. Parthasarathy, Gradient methods for the optimization of dynamical systems containing neural networks IEEE Transactions on Neural Networks. ,vol. 2, pp. 252- 262 ,(1991) , 10.1109/72.80336
P.J. Werbos, Backpropagation through time: what it does and how to do it Proceedings of the IEEE. ,vol. 78, pp. 1550- 1560 ,(1990) , 10.1109/5.58337