Abstract
Variable structure control is a recognized method to stabilize mechanical systems with friction. Friction produces non linear phenomena, such as tracking errors, limit cycles, and undesired stick-slip motion, degrading the performance of the closed-loop system. The main drawback of variable structure control is the presence of chattering, which is not suitable in mechanical systems. In this paper, we design a variable structure controller complemented with Linear-in-the-Parameter neural nets to attenuate chattering. Experimental validation applied to a three degree of freedom robot mechanical manipulator is shown to support the results.
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Guerra, R., Aguilar, L.T., Acho, L. (2007). Chattering Attenuation Using Linear-in-the-Parameter Neural Nets in Variable Structure Control of Robot Manipulators with Friction. In: Castillo, O., Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Hybrid Intelligent Systems. Studies in Fuzziness and Soft Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37421-3_14
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DOI: https://doi.org/10.1007/978-3-540-37421-3_14
Publisher Name: Springer, Berlin, Heidelberg
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