Adaptive Tracking Control of Uncertain Robotic Manipulators in a Constrained Task Space

In this paper, we present adaptive tracking control of uncertain robotic manipulators that operate in a constrained region of the task space. An asymmetric Barrier Lyapunov Function (BLF) is employed to ensure constraint satisfaction in the control design. By allowing the asymmetric barrier limits to vary with the desired trajectory in time, rather than fixing the barrier limit according to a worst case constant bound of the desired trajectory over time, we enlarge the set of feasible initial positions. Despite the derogatory transient effects of online parameter adaptation, asymptotic tracking of a desired trajectory is achieved without the end-effector ever transgressing the constrained region. The performance of the proposed adaptive control is illustrated through simulation.