Dynamic Systems in Neural Networks

Many schemes for the employment of neural networks in control systems have been proposed [9] and some practical applications have also been made [2]. It is possible to apply a neural network to just about every conceivable control problem, however in many cases, although of interest, the network might not be the best or even a good solution, due to its relatively complex nonlinear operation. A neural network is in essence a nonlinear mapping device and in this respect, at the present time, most of the reported work describing the use of neural networks in a control environment is concerned solely with the problem of process modelling or system identification.

[1]  David W. Clarke,et al.  Generalized predictive control - Part I. The basic algorithm , 1987, Autom..

[2]  Kevin Warwick,et al.  Centre Selection for Radial Basis Function Networks , 1995, ICANNGA.

[3]  James S. Albus,et al.  New Approach to Manipulator Control: The Cerebellar Model Articulation Controller (CMAC)1 , 1975 .

[4]  Kevin Warwick,et al.  An overview of neural networks in control applications , 1996 .

[5]  Duc Truong Pham,et al.  Adaptive control of dynamic systems using neural networks , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[6]  P. C. Parks Convergence Properties of Associative Memory Storage for Learning Control Systems , 1992 .

[7]  Kevin Warwick,et al.  A comparative study of multilayered and single layered neural network based predictive controllers , 1992 .

[8]  M. Cuénod Ed. Gerecke 1899-1983 , 1984, Autom..

[9]  Peter J. Gawthrop,et al.  Neural networks for control systems - A survey , 1992, Autom..

[10]  A BortsovYurij,et al.  SELF-TUNING CONTROL , 1991 .

[11]  Patrick C. Parks,et al.  A comparison of five algorithms for the training of CMAC memories for learning control systems , 1992, Autom..

[12]  M. Thoma,et al.  Neurocontrol: Learning Control Systems Inspired by Neuronal Architectures and Human Problem Solving Strategies , 1992 .

[13]  Enis Ersü,et al.  Learning control with interpolating memories―general ideas, design lay-out, theoretical approaches and practical applications , 1992 .

[14]  Andrzej Cichocki,et al.  Neural networks for optimization and signal processing , 1993 .

[15]  Kevin Warwick,et al.  Towards a stability and approximation theory for neuro-controllers , 1994 .

[16]  Václav Peterka,et al.  Predictor-based self-tuning control , 1982, Autom..

[17]  D. Lowe Non-local radial basis functions for forecasting and density estimation , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[18]  David Clarke,et al.  Self-tuning control , 1979 .

[19]  Martin Brown,et al.  Neurofuzzy adaptive modelling and control , 1994 .