A Nonlinear
Output Regulation Perspective on
Autonomous
Helicopter Landing
Department of
Electrical Engineering
The Ohio State
University
Autopilot design for helicopters is a challenging testbed in
nonlinear feedback design, due to
the nonlinearity of the dynamics and the strong coupling between the forces and
torques produced by the vehicle actuators. A helicopter is, in general, an
underactuated mechanical system, that is, it possesses more degrees of freedom
than independent control inputs. This accounts for the presence of a nontrivial
internal dynamics when feedback linearization techniques are applied. In fact,
the resulting zero-dynamics are critically stable, which means that the system
exhibit a non-minimum phase behavior which complicates tremendously the
synthesis of nonlinear control laws. Moreover, the model may be affected by
large uncertainties and unmodelled dynamics. In this talk, we address the
design of an internal-model based autopilot for a helicopter, capable to let
its vertical position follow an exogenous reference signal, while stabilizing
the horizontal and
lateral position and the vehicle attitude to a constant
configuration. The exogenous reference is not supposed to be measured, rather
only the error and its first derivative are accessible to the controller. The
reference signal is given as a sum of a constant term and a fixed number of
sinusoidal signals of unknown frequency, amplitude and phase. This scenario arises when one considers
the problem of letting the helicopter land autonomously on an oscillating
platform, as, for instance, a ship subject to wave-induced oscillations. A
similar problem has been previously considered and solved for a simplified
model of a VTOL aircraft. With respect to the former, however, the present case is more challenging, due to the
higher complexity of the vehicle dynamics which renders the stabilization onto
the desired trajectory a difficult task. We propose a solution which combines
recent results on nonlinear adaptive regulation and robust stabilization of
systems in feedforward form by means of saturated controls. The focus of the
talk is on the design of an adaptive internal model and on the peculiar robust
stabilization technique employed. Due to the intrinsic robustness of the
method, we expect the controller to perform satisfactorily despite the effect
of parametric uncertainties and unmodeled dynamics, as suggested by nonlinear
simulation on a full-order dynamic model.
3:30 – 4:30 p.m.