Abstract
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.
Keywords
- Neural Network
- Radial Basis Function
- Radial Basis Function Network
- Recursive Little Square
- Thin Plate Spline
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Warwick, K., Kambhampati, C., Parks, P., Mason, J. (1995). Dynamic Systems in Neural Networks. In: Hunt, K.J., Irwin, G.R., Warwick, K. (eds) Neural Network Engineering in Dynamic Control Systems. Advances in Industrial Control. Springer, London. https://doi.org/10.1007/978-1-4471-3066-6_2
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DOI: https://doi.org/10.1007/978-1-4471-3066-6_2
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