Abstract
A neural network is used as the feedforward controller in a feedforward-feedback combined system. The network is trained by the feedback output that is minimized during training and most control action for disturbance rejection is finally performed by the rapid feedforward action of the network. The neural feedforward controller is independent of the model of plant and self-adaptive to time-variable system. The dynamic architecture of the neural controller is chosen, and the methods for delay time treatment and training network on line are investigated. An application to oxygen replenishment of an underwater plant is used to prove the effectiveness of the scheme and the simulation shows that the dynamic performance of the oxygen control is greatly improved by this neural combined control system.
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© 2004 Springer-Verlag Berlin Heidelberg
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Zhang, W., Zeng, F., Cheng, G., Gong, S. (2004). Feedforward-Feedback Combined Control System Based on Neural Network. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_17
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DOI: https://doi.org/10.1007/978-3-540-28648-6_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
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