Optimal control for quadrotors during inspection of power utility assets

A. Ailon

 

2019/07/15

Abstract

Renewable energy and power utilities inspection by autonomous aircraft enables rapid and effective risk-free assessment of the state of systems, and provides a qualitative and accurate assessment of defects and damages. To realize maximum operational benefits of aerial inspections, effective
controls for autonomous aircraft must be ensured and the system should be operated in an optimal policy. Hence, the objective of this paper is to consider optimal control strategies for a quadrotor
helicopter type UAV. Based on some structural properties of the considered system, in particular the flatness property, we suggest a control strategy that ensures tracking a time parameterized path
that connects two given points in the state space while minimizing the energy consumption. The proposed controller enables longer-endurance missions for the quadrotor and effective supervision and inspection of large energy systems and power plants. In this paper the analysis of the control law takes into consideration the highly nonlinear dynamic model of the quadrotor and the electrical actuator model. The current approach in solving the optimal control problem under consideration
allows one to eliminate the differential equation and to reformulate the optimal control problem to a nonlinear dynamic programming problem. The approach can make monitoring operations of renewable energy plants by aerial vehicles, more efficient.

Published in: Renewable Energy & Power Quality Journal (RE&PQJ, Nº. 17)
Pages: 85-90 Date of Publication: 2019/07/15
ISSN: 2172-038X Date of Current Version:2019/04/10
REF: 229-19 Issue Date: July 2019
DOI:10.24084/repqj17.229 Publisher: EA4EPQ

Authors and affiliations

A. Ailon
Department of Electrical and Computer Engineering. Ben Gurion University of the Negev, (Israel)
and School of Electrical Engineering

Key words

Aerial inspections for power utilities, quadrotors, nonlinear systems, optimal control, minimum energy.

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