This research outlines the development of an adaptive finite-time fractional-order sliding-mode controller aimed at achieving stabilization and control for the inverted pendulum cart system with limited sensing range of sensors. The proposed algorithm is formulated on the basis of a Barrier Lyapunov function, which unites the benefits of innovative adaptive fractional-order sliding-mode control with a finite-time methodology. The input force is established to stabilize the nonlinear inverted pendulum cart system while adjusting both the position and the pendulum angle to a value of zero. To enhance the robustness of the proposed controller in the face of uncertainties related to the friction and viscous coefficients of the system, these parameters are compensated through an adaptive multi-layer neural-network algorithm. Both the simulation results and the experimental findings validate that the stabilizing controller, which integrates a constrained adaptive finite-time fractional-order sliding-mode control, effectively stabilizes the nonlinear inverted pendulum cart system.
Amir Naderolasli (Mon,) studied this question.