Adaptive tracking control of a robot with model uncertainties and position constraints

An adaptive tracking controller for an n-link robot subject to model uncertainties and position constraints is addressed in this article. The robot's position is constrained in a time-invariant compact set by using the nominal-model-based control scheme, and the position is constrained in a time-varying compact set by utilizing the uncertain-model-based control strategy. It is widely known that certain systems and constant constraints are just special cases in practical engineering, therefore, the uncertain-model-based control method can be more versatile in addressing the practical problems of the robot with state constraints. To prevent constraints from being violated, the barrier Lyapunov function is employed, and the disturbance observer is utilized to estimate the model uncertainty. It can demonstrate the asymptotic stability of the closed-loop systems by utilizing Lyapunov analysis. The effectiveness of the proposed approach is verified by completing the simulation studies.