  With quadrotors becoming immensely popular in applications such as relief
operations, infrastructure maintenance etc., a key control design challenge
arises when the quadrotor has to manoeuvre through constrained spaces during
various operational scenarios: for example, inspecting a pipeline within
predefined velocity and space, dropping relief material at a precise location
under tight spaces etc., under the face of parametric uncertainties and
external disturbances. To tackle such scenarios, a controller needs to ensure a
predefined tracking accuracy so as not to violate the constraints while
simultaneously tackling uncertainties and disturbances. However,
state-of-the-art controllers dealing with constrained system motion are either
not applicable for an underactuated system like quadrotor, or cannot tackle
system uncertainties under full state constraints. This work attempts to fill
such a gap in literature by designing Barrier Lyapunov Function (BLF) based
robust controllers to satisfy multiple state-constraints while simultaneously
negotiating parametric uncertainties and external disturbances. The superiority
of the BLF control method over a typical unconstrained controller is
demonstrated, followed by a robust control design to satisfy position and
orientation constraints on quadrotor dynamics. Finally, full state-constraints
on a quadrotor(i.e., constraints on the position, orientation, linear velocity
and angular velocity) are satisfied with robust control. For each control
design, the closed-loop system stability is studied analytically and the
efficacy of the design is validated extensively either via realistic simulation
scenarios or via experiments performed on a real quadrotor.
