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Implementation of Decentralized Formation Control on Multi-Quadrotor Systems

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Koksal_Nasrettin.pdf (5.48 MB)

Date

2014-04-23

Authors

Koksal, Nasrettin

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University of Waterloo

Abstract

We present real-time autonomous implementations of a practical distributed formation control scheme for a multi-quadrotor system for two different cases: parameters of linearized dynamics are exactly known, and uncertain system parameters. For first case, we design a hierarchical, decentralized controller based on the leader-follower formation approach to control a multi-quadrotor swarm in rigid formation motion. The proposed control approach has a two-level structure: high-level and low-level. At the high level, a distributed control scheme is designed with respect to the relative and global position information of the quadrotor vehicles. In the low-level, we analyze each single quadrotor control design in three parts. The first is a linear quadratic controller for the pitch and roll dynamics of quadrotors. The second is proportional controller for the yaw motion. The third is proportional-integral-derivative controller in altitude model. For the second case, where inertial uncertainties in the pitch and roll dynamics of quadrotors are considered, we design an on-line parameter estimation with the least squares approach, keeping the yaw, altitude and the high-level controllers the same as the first case. An adaptive linear quadratic controller is then designed to be used with lookup table based on the estimation of uncertain parameters. Additionally, we study on enhancement of self and inter-agent relative localization of the quadrotor agents using a single-view distance-estimation based localization methodology as a practical and inexpensive tool to be used in indoor environments for future works. Throughout the formation control implementations, the controllers successfully satisfy the objective of formation maintenance for non-adaptive and adaptive cases. Simulations and experimental results are presented considering various scenarios, and positive results obtained for the effectiveness of our algorithm.

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Keywords

Formation control, adaptive control, unmanned vehicles

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http://hdl.handle.net/10012/8338

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Theses
Mechanical and Mechatronics Engineering