Design of an intelligent fault-tolerant control system for an unmanned aerial vehicle
Date
2015-05-12
Authors
Higgs, Duncan
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Abstract
An intelligent fault-tolerant control system for an unmanned aerial vehicle was developed that was
designed to be capable of tolerating a number of different control actuator faults. The development of
the control system focused on the simulation of the system using a nonlinear flight dynamic model
with the aim to implement this control strategy in an operational UAS in the future. The nonlinear
flight dynamic model was a high fidelity, six-degree-of-freedom model that made use of available
wind tunnel data. The model considered the general equations of motion of an asymmetric rigid
aircraft within the troposphere and also considered motor, and control actuator dynamics. The
proposed control strategy consisted of a model reference fuzzy logic adaption algorithm combined
with a daisy chain allocation algorithm. An equivalent desired first order behaviour was used to
generate an ideal response to a control input and used as a reference for the adaption algorithm to
follow. The allocation algorithm made use of secondary and tertiary control effectors that were used
only after the primary control surface reached its physical limits of travel. A number of control
actuator failures, of varying severity, were modelled that included elevator failures, aileron failures
and combined aileron and elevator failures. The results showed the proposed control system was
better able to tolerate the simulated failures when compared to the unmodified autopilot. For more
severe failures it was found that the control allocation algorithm was a necessity and in some cases the
adaption algorithm when used in isolation, induced control instability. Tuning of the adaption rates of
the adaption algorithm was found to have a significant effect on the performance of the system. In
some cases the incorrect adaption rate caused degraded control performance. It was, however,
concluded that the proposed control strategy did provide a degree of fault-tolerance for the failure
scenarios considered. It is recommended that research into the effects of adaption rates, auxiliary
control functions (such as feedforward loops) and the use of health monitoring be considered for a
more practical system. It is also recommended that extensive testing be conducted with hardware in
the loop simulators before this system be implemented.