  This paper investigates adaptive control of nonlinear robot manipulators with
parametric uncertainty. Motivated by generating closed-loop robot dynamics with
enhanced transmission capability of a reference torque and with connection to
linear dynamics, we develop a new adaptive approach by exploiting
forwardstepping design and inertia invariance, yielding differential-cascaded
closed-loop dynamics. With this approach, we propose a new class of adaptive
controllers for nonlinear robot manipulators. Our particular study concerning
adaptive control of robots exhibits a design methodology towards establishing
the connection between adaptive control of highly nonlinear uncertain systems
(e.g., with a variable inertia matrix) and linear dynamics (typically with the
same or increased order), which is a long-standing intractable issue in the
literature.
