The aim of this study is developing a robust controller with state dependent gains which guarantees the fixed-time robust convergence of the tracking error trajectories at each articulation for a suspended biped robot. The satisfaction of the state restrictions is justified with the controller gains design that are calculated using a Barrier tangent-type Lyapunov candidate function. The explicit adaptation law is obtained with the analysis of the controlled variant of the Barrier function, including the deviation terms for the selected adaptive gains. The virtualized model of the biped robot serves as a testing platform for the suggested controller, this computer-aided model robot operates as numerical test bench for the robust constraint controller. Some numerical simulation demonstrate the application of the state feedback controller with state restrictions and the gain law. The comparison of the tracking performance implementing the suggested controller and the regular proportional-integral-derivative form confirms the origin as a fixed-time stable equilibrium point for the tracking error while the state space restrictions are satisfied.