Abstract
Quadrotor unmanned aerial vehicles (UAVs) have attracted considerable interest for various applications including search and rescue, environmental monitoring, and surveillance because of their agilities and small sizes. This paper proposes trajectory tracking control of UAVs utilizing online iterative learning control (ILC) methods that are known to be powerful for tasks performed repeatedly. PD online ILC and switching gain PD online ILC are used to perform a variety of manoeuvring such as take-off, smooth translation, and various circular trajectory motions in two and three dimensions. Simulation results prove the ability and effectiveness of the online ILCs to perform successfully certain missions in the presence of disturbances and uncertainties. It also demonstrates that the switching gain PD ILC is much effective than the PD online ILC in terms of fast convergence rates and smaller tracking errors.
Highlights
Unmanned aerial vehicles (UAVs) have become very popular among researchers and developers in the last decade, owing to their capabilities of various applications such as meteorological surveillance, disaster monitoring, and military purposes
The contribution of this work to the UAV field consists in the exploration of different online iterative learning control (ILC) on trajectory tracking control of quadrotor UAVs for the first time, focusing on performance improvements under conditions of uncertainty and disturbances
It demonstrates the effectiveness of the online ILCs and the better tacking performance obtained by the SPD online ILC
Summary
Unmanned aerial vehicles (UAVs) have become very popular among researchers and developers in the last decade, owing to their capabilities of various applications such as meteorological surveillance, disaster monitoring, and military purposes. Based on gain-scheduling control theory, the nonlinear problem of UAV dynamics was represented as piece-wise error dynamics over a predefined set of operating regions in [35], and the design and performance evaluation of a trajectory tracking controller were discussed. To the best of our knowledge, there is rare application of ILC on the control of UAVs. The contribution of this work to the UAV field consists in the exploration of different online ILCs on trajectory tracking control of quadrotor UAVs for the first time, focusing on performance improvements under conditions of uncertainty and disturbances. The research can be viewed as a new application of online ILCs. In this research, two competitive types of ILCs, namely, PD online ILC and switching gain PD (SPD online ILC), are employed in order to control a quadrotor UAV to follow various desired trajectories in the presence of disturbances and uncertainties. Simulations are conducted to verify the capability of performing various missions repeatedly with some constraints
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