AUTHOR=Qian Xiaoshan , Xu Lisha , Yuan Xinmei 

TITLE=Fuzzy super twisting mode control of a rigid-flexible robotic arm based on approximate inertial manifold dimensionality reduction

JOURNAL=Frontiers in Neurorobotics

VOLUME=Volume 17 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2023.1303700

DOI=10.3389/fnbot.2023.1303700

ISSN=1662-5218

ABSTRACT=This paper addresses the challenges related to poor control quality of the directly truncated 4 first-order modal model of an infinite-dimensional rigid-flexible robotic arm and the relative 5 complexity of hardware implementation of the directly truncated second-order modal model 6 controller. A fuzzy super twisting mode control method based on the approximate inertial manifold 7 dimensionality reduction model of the rigid-flexible robotic arm is proposed. This method can 8 ensure high control quality while simplifying the hardware implementation of the controller.  We first introduce an adjustable exponential non-singular sliding surface, combined with a stable continuous super twisting algorithm. By modifying the nonlinear homogeneous sliding surface, finite-time convergence is achieved. Using a new fuzzy strategy, the sliding surface coefficient is dynamically optimized in real-time. Compared with the fuzzy method for sliding mode exponent, it is simpler and easier to implement. Based on Lyapunov theory, the stability of the system is then proven. Finally, various simulation and experimental results demonstrate that compared to the directly truncated first-order and second-order modal models, the proposed method is effective, has good tracking performance under bounded external disturbances, strong robustness, and simplifies the controller design while ensuring high control quality.