  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 the proposed 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.
