Multiresolution Controller Based on Window Function Networks for a Quanser Helicopter
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Springer Nature Switzerland
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https://link.springer.com/content/pdf/10.1007/978-3-031-47765-2_4
Reference19 articles.
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2. Chen, S., Billings, S.A.: Neural networks for nonlinear dynamic system modelling and identification. Int. J. Control 56(2), 319–346 (1992). https://doi.org/10.1080/00207179208934317
3. Díaz López, F.A., Ramos Velasco, L.E., Domínguez Ramírez, O.A., Parra Vega, V.: Multiresolution wavenet PID control for global regulation of robots. In: 9th Asian Control Conference (ASCC 2013), 23–26 June 2013, Istanbul, Turkey, pp. 1–6. IEEE (2013). https://doi.org/10.1109/ASCC.2013.6606328
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5. Garcia-Castro, O.F., et al.: RBF neural network based on FT-windows for auto-tunning PID controller. In: Advances in Computational Intelligence, pp. 138–149. Springer Nature, Switzerland (2022). https://doi.org/10.1007/978-3-031-19493-1_11
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