Abstract
A model following adaptive controller made-up by neural networks is proposed to control the angular displacement of swashplate in a variable displacement axial piston pump (VDAPP), which consists of multiple neural networks including a direct neural controller, a neural emulator and a neural tuner. The controls of swashplate angle are investigated by simulation and experiment, serve its model-following characteristics can be evaluated and compared with other methods.
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© 2006 Springer-Verlag Berlin Heidelberg
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Chu, MH., Kang, Y., Liu, YL., Chen, YW., Chang, YP. (2006). An Adaptive Control Using Multiple Neural Networks for the Variable Displacement Pump. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_82
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DOI: https://doi.org/10.1007/11779568_82
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35453-6
Online ISBN: 978-3-540-35454-3
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