Abstract
In this work it is presented the design of a decentralized adaptive fuzzy control. In this scheme it is suppose a system with unknown parameters and on-line fuzzy identifier, which uses an adaptive law to adjust the unknown parameters in order to build a model of an assumed unknown nonlinear system. The applicability of the proposed approach is illustrated via simulations by trajectory tracking control of a two degrees-of-freedom robot manipulator.
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Canul, R.C., Garcia-Hernandez, R., Rullan-Lara, J.L., Llama, M.A. (2014). Decentralized Adaptive Fuzzy Control Applied to a Robot Manipulator. In: Jamshidi, M., Kreinovich, V., Kacprzyk, J. (eds) Advance Trends in Soft Computing. Studies in Fuzziness and Soft Computing, vol 312. Springer, Cham. https://doi.org/10.1007/978-3-319-03674-8_12
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DOI: https://doi.org/10.1007/978-3-319-03674-8_12
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03673-1
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