Singularity-Free Adaptive Fixed-Time Tracking Control for MIMO Nonlinear Systems With Dynamic Uncertainties.

This brief focuses on adaptive neural fixed-time tracking control problem for the multi-input and multi-output (MIMO) nonlinear systems with dynamic uncertainty. In the controller design process, the difficulties are to overcome the multiple singularity problems. The hyperbolic tangent function and the piecewise function are invoked to deal with the singularity problems that occur in the process of realizing the fixed-time stability of the dynamic signal and designing the control signal, respectively. By mean of fixed-time stability theorem, the presented controller can ensure the boundedness of all closed-loop signals (CLS) and the ideal tracking performance in a period of fixed-time. Simulation results test the feasibility of the presented algorithm.