Journal article
Fuzzy Self-Tuning of Strictly Negative-Imaginary Controllers for Trajectory Tracking of a Quadcopter Unmanned Aerial Vehicle
IEEE transactions on industrial electronics (1982), Vol.68(6), pp.5036-5045
06/2021
Metrics
3 Record Views
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Source: InCites
Abstract
Robustness in the face of uncertainties is an integral part of designing a real-time control system. Based on negative imaginary (NI) systems theory, we design robust and adaptive control systems for accurate trajectory tracking of a quadcopter aerial vehicle. Considering the challenging dynamics of unmanned aerial vehicles, we employ knowledge-based fuzzy inference systems (FIS) to facilitate automatic tuning in our SNI controllers, leading to the development of adaptive SNI control systems. Unlike fixed-gain controllers that have no ability to adapt to the variations in environmental conditions or changes in the dynamics of the plant, our adaptive SNI controllers are able to perform self-tuning to constantly update their parameters. The concept of adaptive autopilots will enhance the ability of the closed-loop control systems to accommodate large uncertainties. To demonstrate their efficacy, we design and implement our adaptive SNI controllers in the three-position control loops of the AR.Drone quadcopter after conducting extensive computer simulations. We also perform a rigorous comparative study with respect to the performance of fixed-gain SNI controllers, fixed-gain NI systems, in addition to model-predictive-control systems, and proportional integral derivative (PID) control systems as our benchmarks. To complete the study, we conduct a stability analysis based on Kharitonov's Theorem.
Details
- Title
- Fuzzy Self-Tuning of Strictly Negative-Imaginary Controllers for Trajectory Tracking of a Quadcopter Unmanned Aerial Vehicle
- Creators
- Vu Phi Tran - University of New South WalesFendy Santoso - University of New South WalesMatthew A. Garratt - University of New South WalesIan R. Petersen - Australian National University
- Publication Details
- IEEE transactions on industrial electronics (1982), Vol.68(6), pp.5036-5045
- Publisher
- IEEE
- Grant note
- Internal Research grant from UNSW Canberra, Australia
- Identifiers
- 991013092674602368
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article