Robust Hierarchical Adaptive Fuzzy Relative Motion Coordination for Feature Points of Two Rigid Bodies With Input and Output Constraints

In this article, a model-based six-degrees-of-freedom relative motion coordinated control approach is developed for the relative position tracking and attitude synchronization between feature points of two rigid bodies subject to control input constraints, output constraints, and model uncertainties. In the designing framework of adaptive backstepping control technique, the control input saturation is compensated by the nonlinear antiwindup compensator and the output constraints are handled by the barrier Lyapunov function-based backstepping design. The unknown misalignment vector of the feature point with respect to the center of the mass for the chaser is estimated by the element-wise adaptive law, while the model uncertainties and unknown dynamical couplings are compensated by the adaptive hierarchical fuzzy logic system to decrease the computational burden with respect to the traditional adaptive fuzzy system. The ultimately uniformly bounded convergence of the relative pose and relative velocities is analyzed in the Lyapunov framework and the effectiveness of the proposed approach is validated by the numerical simulations.