A Self-Evolving Neural Network-Based Finite-Time Control Technique for Tracking and Vibration Suppression of a Carbon Nanotube

The control of micro- and nanoscale systems is a vital yet challenging endeavor because their small size high sensitivity, which make them susceptible to environmental factors such as temperature humidity. Despite promising methods proposed for these in literature, the chattering controller, convergence time, robustness against wide range disturbances still require further attention. To tackle this issue, we present an intelligent observer, accounts uncertainties disturbances, along with chatter-free controller. First, dynamics carbon nanotube (CNT) are examined, its governing equations outlined. Then, design controller described. approach incorporates self-evolving neural network-based methodology super-twisting sliding mode technique eliminate uncertainties’ destructive effects. Also, ensures finite-time system. then implemented on CNT effectiveness different conditions investigated. numerical simulations demonstrate method’s outstanding performance both stabilization tracking control, even presence uncertain parameters system complicated disturbances.