An Integrated, Multi-Layer Approach to Software-Enabled Control:
Mission Planning to Vehicle Control
Project Summary: 2000
Objective:
The objective of this project is development of a unified design framework to
synthesize and simulate individual vehicle management systems. This program
uses innovations in nonlinear control, fault detection, reconfiguration and
tactical trajectory generation to advance technologies associated with command
and control of a Uninhabited Air Vehicle (UAV). The goal is to embed in the
on-board vehicle management system significant high level functionality to
extend the autonomy and lifetime of UAVs.
Approach:
Theory, algorithms and software modules are being developed under this
program for on-line control customization of Uninhabited Air Vehicles
(UAVs). On-line control customization (OCC) will enable a dramatic increase
in military effectiveness by increasing the level of autonomy in UAVs and the
probability of mission success and survivability, and by expanding the range of
UAV missions while reducing air vehicle fatigue and life cycle costs. The benefits
to the military of OCC advances include use of extremely aggressive
maneuvering of UAVs to achieve mission directives, accommodation of goal
changes in real-time, life-extending control, and a reduced need for hardware
redundancy while allowing more complex control strategies without increased
software production and verification costs. A key component of our research is
the integration of our OCC algorithms into the Open Control Platform (OCP)
software infrastructure.
Our approach to individual vehicle control is to blend on-line optimization with
off-line robust, nonlinear controllers. Both approaches to control require an
accurate model of the nonlinear dynamics of the UAV. The off-line controllers
will be designed using linear, parameter varying (LPV) control techniques. The
benefit of LPV synthesis techniques is that very aggressive, multivariable
inner-loop flight controllers can be synthesized off-line that guarantee stability
of a large subset of the nonlinear flight envelope. In addition to the standard
tracking and disturbance rejection flight control performance objectives, LPV
controllers can be synthesized that schedule in real-time as a function of overall
mission objectives, i.e. threats, failure, environment, longevity. The LPV
framework has also been extended to allow for variable sample-time
implementation of the controller. Real-time implementation of LPV controllers
is similar to existing gain-scheduled controllers and therefore can be directly
integrated within the OCP software infrastructure.
The on-line control technique combines receding horizon control (RHC), which
solves an optimal open-loop receding-horizon problem, with the closed-loop
Lyapunov functions (CLF) generated by the LPV design. The LPV CLF is used as
a final cost penalty in the RHC optimization. The combination of RHC with a
stabilizing CLF final cost penalty provides a stability guarantee for the RHC
controller. The RHC optimization is based on full state feedback with set point
regulation and doesn't include plant and model mismatch, external disturbances,
command tracking and state operability constraints. RHC uses the full nonlinear
model of the UAV to solve for the "optimal" control inputs on-line. Hence, RHC
provides real-time adaptation to mission goals, changes in the system dynamic,
constraints, and environmental factors and disturbances provided appropriate
CLFs can be defined for each scenario. RHC will add significant autonomy to the
UAV allowing event-based RHC for mission reconfiguration, smart allocation of
resources, event-driven reconfiguration due to either mission requirements or
system/component failures as well as performance customization.
To validate the proposed control design approaches, a public domain model of an
F-16 aircraft, based on NASA Technical Paper 1538, was constructed to serve as
our UAV. The baseline F-16 Block A controller was included in the nonlinear
simulation for comparison. A quasi-LPV model of the nonlinear aircraft
dynamics was synthesized and used to design an LPV inner-loop flight controller
for the up and away flight envelope. Off-line LPV controllers have been
synthesized that schedule on altitude, Mach number, angle-of-attack and
mission level goals. RHC/LPV full state feedback controllers have been
synthesized that show a performance improvement based on the ideal, nonlinear
airframe model.