Improved Performance in Quadrotor Trajectory Tracking using MIMO PIλ-D Control

Vivek Pawan Shankaran; Sheikh Izzal Azid; Utkal Mehta; Adriano Fagiolini

doi:10.1109/ACCESS.2022.3214810

Back

Improved Performance in Quadrotor Trajectory Tracking using MIMO PIλ-D Control

Journal article

Open access

Peer reviewed

Improved Performance in Quadrotor Trajectory Tracking using MIMO PIλ-D Control

Vivek Pawan Shankaran, Sheikh Izzal Azid, Utkal Mehta and Adriano Fagiolini

IEEE access, Vol.10, pp.110646-110660

2022

DOI: https://doi.org/10.1109/ACCESS.2022.3214810

Files and links (1)

pdf

Published5.64 MBDownload View

CC BY V4.0, Open Access

Abstract

Boundary conditions

Fractional-order control

MIMO communication

MIMO system

Optimization

PD control

Quadrotor

Real-time

Real-time systems

Rotors

Sliding mode control

Stability boundary surface

Trajectory tracking

Tuning

This paper aims to develop a fractional control approach for quadrotor trajectory tracking. A fractional-order integrator (PI λ ) with a feedback derivative scheme is designed to control each state of the MIMO system. The designed feedback controller stabilizes the initially unstable decoupled states and widens the stability, while PI λ provides precise trajectory tracking capabilities. After a successful simulation study, the new PI λ -D controller is implemented in the hardware environment. The various performance and load disturbance analyses reveal the effectiveness of the proposed scheme compared with the classical PD/PID controllers. The real-time study also shows that this scheme is a simple yet robust solution.

Details

Title: Improved Performance in Quadrotor Trajectory Tracking using MIMO PIλ-D Control
Authors/Creators: Vivek Pawan Shankaran - University of the South Pacific
Sheikh Izzal Azid - Charles Darwin University
Utkal Mehta - University of the South Pacific
Adriano Fagiolini - University of Palermo
Publication Details: IEEE access, Vol.10, pp.110646-110660
Publisher: IEEE
Grant note: The University of the South Pacific
Identifiers: 991005654370107891
Murdoch Affiliation: Murdoch University
Language: English
Resource Type: Journal article

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Source: InCites

Metrics

1 File views/ downloads

69 Record Views

14 Times Cited - Web of Science

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Domestic collaboration; International collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.29 Automation & Control Systems; 4.29.104 Adaptive Control
Web Of Science research areas: Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications
ESI research areas: Engineering