In this article

a practical fixed-time adaptive fuzzy control strategy is investigated for uncertain nonlinear systems with time-varying asymmetric constraints and input quantization. To overcome the difficulties of designing controllers under the state constraints case

a unified barrier function approach is employed to construct a coordinate transformation that maps the original constrained system to be an equivalent unconstrained one

thus relaxing the time-varying asymmetric constraints upon system states and avoiding the feasibility check condition typically required in the traditional barrier Lyapunov function-based control approach. Meanwhile

the“explosion of complexity” problem in the traditional backstepping approach arising from repeatedly derivatives of virtual controllers is solved by using the command filter method. It is verified via the fixed-time Lyapunov stability criterion that the system output can track a desired signal within a small error range in a predetermined time

and all system states remain in the constraint range. Finally

a simulation example is offered to demonstrate the effectiveness of the proposed strategy.