Neuroadaptive Asymptotic Tracking Control of Nonlinear Systems with Multiple Uncertainties

Guichao Yang ()
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Guichao Yang: School of Mechanical and Power Engineering, Nanjing Tech University, Nanjing 211816, China

Mathematics, 2023, vol. 11, issue 13, 1-12

Abstract: In this work, several innovative robust neuroadaptive control algorithms are integrated via the command filtered backstepping approach for a class of mismatched uncertain nonlinear systems. They utilize neural network adaptive control to achieve an enhanced model compensation effect. In addition, different robust terms with a positive time-varying integral expression are synthesized for each of the algorithms to address external disturbances. Each of the synthesized control algorithms has a continuous control input and cannot only remove the adverse effects of the “explosion of complexity” inherent in the traditional backstepping technology but also produce an asymptotic tracking result for the closed-loop system via strict theoretical analysis. Comparative simulation verifications are implemented to check the feasibility and practicability of the presented controllers.

Keywords: modeling uncertainty; motion control; asymptotic tracking; adaptive control; robust control; neural networks (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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