A Decentralized Low-Chattering Sliding Mode Formation Flight Controller for a Swarm of UAVs

Abstract

In this paper, a nonlinear robust formation flight controller for a swarm of unmanned aerial vehicles (UAVs) is presented. It is based on the virtual leader approach and is capable of achieving and maintaining a formation with time-varying shape. By using a decentralized architecture, the local controller in each UAV uses information only from the UAV itself, its neighbors, and from the virtual leader. Also, a synchronization control objective provides a mechanism to weight between the fleet achieving the desired formation shape, that is, achieving the desired relative position between the UAVs, and each UAV achieving its desired absolute position. The use of a combination of a sliding mode controller and a low pass filter reduces the usual chattering effect, providing a smooth control signal while maintaining robustness. Simulation results show the effectiveness of the proposed decentralized controller.

UAV Multi-Dynamic Target Interception: A Hybrid Intelligent Method Using Deep Reinforcement Learning and Fuzzy Logic

“…When applying this hybrid controller for real flight tests, even though most quadrotors may not be as sensitive to fluctuating signals, such volatility could still cause mechanical wear and potentially pose a risk. Cordeiro et al [49] designed a sliding-mode controller (SMC) for fixed-wing UAVs and effectively smoothed the highly fluctuated control signals by incorporating a low-pass filter, reducing common chattering effects while ensuring robustness. In [50], the authors employed an extended Kalman filter (EKF) within their proposed controller.…”

Optimization and Communication in UAV Networks

“…Although bringing more performances in terms of coverage and connectivity, new optimization challenges pop up due to the difficulty to control and scale such swarms both in a distributed or centralized way. References [ 5 , 6 , 7 , 8 ] tackle these numerous challenges going from connectivity maintenance to swarm control.…”

“…The authors thus introduce a UAV replacement procedure as a way to guarantee ground users’ connectivity over time, formulating the practical UAV replacements problem in moderately large multi-UAV swarms and proves it to be an NP-hard problem in which an optimal solution has exponential complexity. Reference [ 7 ] focuses on the maintenance formation with time-varying shape of a swarm proposing a virtual leader approach while [ 8 ] investigates a stochastic model of the UAV Swarm system with multiplicative noises.…”