An adaptive sliding mode controller for a class of MIMO Euler-Lagrange systems with variable parameters
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https://doi.org/10.54939/1859-1043.j.mst.79.2022.1-9Keywords:
Euler-Lagarance systems; Adaptive sliding-mode control; RBF neural network.Abstract
This paper presents a method to synthesize the adaptive sliding mode controller for a class of MIMO Euler-Lagarance systems with variable parameters. We perform a Taylor series expansion of a class of MIMO Euler-Lagarance systems into nonlinear state-space equations, considering cases of varying parameters and unmeasured external disturbances. We propose a method to identify and compensate for variable components, external disturbance based on adaptive control theory, and RBF neural network to make the system invariant to these uncertain changing components. We build the control law based on sliding mode control. The research results of the paper obtained are that the adaptive sliding mode controller is adaptive, resistant to interference, and has high control quality.
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