Abstract
A novel dynamic control allocation method is proposed for a small fixed-wing unmanned aerial vehicle (UAV), whose flaps can be actuated as fast as other control surfaces, offering an extra way of changing the lift directly. The actuator dynamics of this kind of UAVs, which may be sluggish comparing with the UAV dynamics, should also be considered in the control design. To this end, a hierarchical control allocation architecture is developed. A disturbance observer-based high-level tracking controller is first designed to accommodate the lagging effect of the actuators and to compensate the adverse effect of external disturbances. Then, a dynamic control allocator based on a receding-horizon performance index is developed, which forces the actuator state in the low level to follow the optimized reference. Compared with the conventional control allocation method that assumes ideal actuators with infinite bandwidths, higher tracking accuracy of the UAV and better energy efficiency can be achieved by the proposed method. Stability analysis and high-fidelity simulations both demonstrate the effectiveness of the proposed method, which can be deployed on different fixed-wing UAVs with flaps to achieve better performance.
Highlights
R ECENT decades have witnessed the rapid growth on both the development and application of small unmanned aerial vehicles (UAVs) in different domains, ranging from surveillance, payload delivery to environmental monitoring and agriculture mapping
A new actuator-dynamics-based dynamic control allocation scheme is developed for flight control of a small fixed-wing UAV with direct lift control (DLC) to compensate unknown external disturbances
Compared to the conventional UAVs, the considered small UAV presents faster dynamics, the actuator dynamics cannot be ignored in high-precision applications
Summary
R ECENT decades have witnessed the rapid growth on both the development and application of small unmanned aerial vehicles (UAVs) in different domains, ranging from surveillance, payload delivery to environmental monitoring and agriculture mapping. Some control oriented techniques [1]–[4] have been investigated to compensate the wind disturbances This paper approaches this problem from a different perspective, by exploiting the flight mechanism of conventional fixed-wing UAVs equipped with dedicated flaps. Apart from the basic control allocation functions, many advanced algorithms have considered additional factors, e.g., actuator energy saving and actuator safety, using techniques such as linear/nonlinear constrained quadratic programming [13], [14], additional dynamic augmentation [15] and input matrix factorization [16] Those control allocation methods may not be readily applicable to the problem investigated in this work due to the presence of slow actuator dynamics. Matrix 0i× j denotes an i × j zero matrix and matrix 1k×k denotes a k × k identity matrix
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