Adaptive Trajectory Tracking for Quadrotor Systems in Unknown Wind Environments Using Particle Swarm Optimization-Based Strictly Negative Imaginary Controllers
Vu Phi Tran, Fendy Santoso, Matthew Garratt
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.