Abstract
For control of strongly nonlinear electromechanical actuator, it is useful to use composite regulator consisting of a PID and feedforward and/or feedback nonlinearities compensator. In this article, we show the application of Receptive Field Weighted Regression for approximation of reduced inverse dynamic model of the actuator. This model neglects the effect of inertia in the model of the actuator, which solves the problem of difficulty related to practical measurement/estimation of the acceleration from the measured positions. The resulting controller is able to self-tune and further adapt to the changes of parameters due to wear, temperature and other environmental conditions.
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Grepl, R., Sova, V., Chalupa, J. (2016). Adaptive Control of Electro-Mechanical Actuator using Receptive Field Weighted Regression. In: Jabłoński, R., Brezina, T. (eds) Advanced Mechatronics Solutions. Advances in Intelligent Systems and Computing, vol 393. Springer, Cham. https://doi.org/10.1007/978-3-319-23923-1_87
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DOI: https://doi.org/10.1007/978-3-319-23923-1_87
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