Journal article
Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers
IEEE transactions on aerospace and electronic systems, Vol.57(3), pp.1742-1752
06/2021
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Abstract
Leveraging the benefits of the multiobjective particle swarm optimization (PSO) technique, we introduce a new concept of adaptive strictly negative imaginary (SNI) controllers. The proposed adaptive control systems are specifically designed to minimize a certain performance index, representing the objective of our control design, which is to obtain a stable, robust, and responsive 3-D tracking of the AR.Drone drone in the face of wind gusts. We compare the performance of our proposed adaptive controllers with respect to the performance of PSO-PID control systems and the traditional Ziegler-Nichols PID controllers, not only in simulated flights but also in real flight tests. We also present a stability analysis of the closed-loop control system using the SNI system theory.
Details
- Title
- Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers
- Creators
- Vu Phi Tran - University of New South WalesFendy Santoso - University of New South WalesMatthew A. Garratt - University of New South Wales
- Publication Details
- IEEE transactions on aerospace and electronic systems, Vol.57(3), pp.1742-1752
- Publisher
- IEEE
- Grant note
- UNSW Canberra, Australia
- Identifiers
- 991013092522902368
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Journal article