Abstract
Wind disturbances and noise severely affect Unmanned Aerial Vehicles (UAV) when monitoring and finding faults in overhead power lines. Accordingly, we propose repetitive learning as a new solution for the problem. In particular, the performance of Iterative Learning Control (ILC) that are based on optimal approaches are examined, namely (i) Gradient-based ILC and (ii) Norm Optimal ILC. When considering the repetitive nature of fault-finding tasks for electrical overhead power lines, this study develops, implements and evaluates optimal ILC algorithms for a UAV model. Moreover, we suggest attempting a learning gain variation on the standard optimal algorithms instead of heuristically selecting from the previous range. The results of both simulations and experiments of gradient-based norm optimal control reveal that the proposed ILC algorithm has not only contributed to good trajectory tracking, but also good convergence speed and the ability to cope with exogenous disturbances such as wind gusts.
Highlights
Overhead electrical power lines are a vital component of the power supply infrastructure
We suggest attempting a learning gain variation on the standard optimal algorithms instead of heuristically selecting from the previous range. The results of both simulations and experiments of gradient-based norm optimal control reveal that the proposed Iterative Learning Control (ILC) algorithm has contributed to good trajectory tracking, and good convergence speed and the ability to cope with exogenous disturbances such as wind gusts
Note that the implementation of optimal algorithms in such cases needs to be investigated. This is more crucial in the application of Unmanned Aerial Vehicles (UAV) for the monitoring overhead power system, especially since the quadrotor UAV has more than one degree of freedom
Summary
Overhead electrical power lines are a vital component of the power supply infrastructure. Some depend on classical control (e.g., PID controller), which is simple and capable of providing acceptable performance [11] Others are based on non-linear control such as sliding-mode [13] or back-stepping [14] These works make use of conventional feedback and feedforward and to improve the control performance by augmenting the previous controllers (i.e., PID controller). This paper seeks to determine whether the proposed optimal algorithms can be applied to quadrotors for tracking performance. It proceeds to motivate, develop, and evaluate the flight controller required to address and if it can address this deficiency of these previous methods.
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