Adaptive Radial-Basis Function Neural Network Control of a Pneumatic Actuator
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-4725-6_32
Reference15 articles.
1. Andrikopoulos, G., Nikolakopoulos, G., Manesis, S.: Advanced nonlinear PID-based antagonistic control for pneumatic muscle actuators. IEEE Trans. Ind. Electron. 61(12), 6926–6937 (2014). https://doi.org/10.1109/TIE.2014.2316255
2. Anh, H.P.H., Ahn, K.K.: Hybrid control of a pneumatic artificial muscle (PAM) robot arm using an inverse NARX fuzzy model. Eng. Appl. Artif. Intell. 24(4), 697–716 (2011). https://doi.org/10.1016/j.engappai.2010.11.007
3. Banala, S.K., Kim, S.H., Agrawal, S.K., Scholz, J.P.: Robot assisted gait training with active leg exoskeleton (ALEX). IEEE Trans. Neural Syst. Rehabil. Eng. 17(1), 2–8 (2009). https://doi.org/10.1109/TNSRE.2008.2008280
4. Carvalho, A.D.D.R., Karanth P, N., Desai, V.: Characterization of pneumatic muscle actuators and their implementation on an elbow exoskeleton with a novel hinge design. Sens. Actuators Rep. 4, 100109 (2022). https://doi.org/10.1016/j.snr.2022.100109
5. Chan, S., Lilly, J., Repperger, D., Berlin, J.: Fuzzy PD+I learning control for a pneumatic muscle. In: The 12th IEEE International Conference on Fuzzy Systems, 2003. FUZZ ’03, vol. 1, pp. 278–283 (2003). https://doi.org/10.1109/FUZZ.2003.1209375
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