Adaptive Shared Trajectory Tracking Control for Output-Constrained Euler–Lagrange Systems

This study presents the state-feedback and output-feedback adaptive shared trajectory tracking control laws for nonlinear Euler–Lagrange systems subject to parametric uncertainties and output constraints framed within linear inequalities. The logarithm-driven coordinate transformation is used to ensure that system outputs are consistently bounded by defined regions, while model-based adaptive laws are used in the machine controller to estimate and cancel parametric uncertainties and the human controller can be given arbitrarily. The stability of the whole controlled system is proved by Lyapunov stability theory, and simulation examples are used to illustrate the performance of the proposed shared control laws.