Adaptive Improved Practical Finite‐Time Tracking Strategy for MIMO Stochastic Nonlinear Systems and Its Application in Flexible Robotic Manipulator

This article proposes an improved command‐filtered adaptive practical fast finite‐time tracking strategy for multi‐input multi‐output (MIMO) stochastic nonlinear systems. Compared to existing approaches, it targets three critical unresolved challenges: (1) intermittent output constraints active only during finite intervals, (2) control singularity in finite‐time backstepping designs, and (3) synergistic handling of concurrent practical imperfections. To address these challenges, a shift‐barrier function combination enables seamless constraint transitions, a piecewise continuous function guarantees singularity‐free control, an innovative disturbance observer estimates unknown disturbances, and Pade approximation mitigates input delay. Theoretical analysis confirms all closed‐loop signals are bounded in probability while satisfying intermittent constraints. In the end, to demonstrate the effectiveness of the proposed strategy, the method is applied to a 2‐link flexible robotic manipulator (FRM) that tracks different trajectories.