Distributed fault-tolerant formation control for multiple unmanned aerial vehicles under actuator fault and intermittent communication interrupt

Abstract

This article develops a distributed adaptive fault-tolerant formation control scheme for the multiple unmanned aerial vehicles to counteract actuator faults and intermittent communication interrupt, where the issues on control input saturation and mismatched uncertainties are also addressed. The discontinuous communication protocol technique is exploited to achieve the stability of the formation system, if the conditions of dwell time and the rate of communication are satisfied. On the basis of the local information of neighboring unmanned aerial vehicles, a novel distributed adaptive mechanism is designed to estimate the bounds of actuator faults and uncertainties, where the input saturation is explicitly taken into consideration. The stability of the whole formation system under the designed fault-tolerant formation control strategy is analyzed using the Lyapunov approach. Finally, simulation results are presented to illustrate the effectiveness of the proposed scheme.

Neural network–based optimal fault compensation control of the nonlinear multi-agent system and its application to UAVs formation flight

“…Theorem 2. Let us consider system (3) with G i = 0 (that is, system (3) is fault-free) under Assumptions 1-3, then the updating laws of CNN (22) can guarantee that weight approximate errors Wi , i 2 V are uniformly ultimately bounded (UUB).…”

“…21 The problems of input saturations and uncertainties are considered, and the distributed adaptive FTC method is developed based on a discontinuous communication protocol to ensure the stability of UAVs. 22 Although previous works have studied the FTC problem for UAV formation systems, they still have not taken the optimality into consideration. For UAV formation systems, nevertheless, the research on optimal FTC problems is always so significant, which prompts us to investigate further.…”

Adaptation Strategy for a Distributed Autonomous UAV Formation in Case of Aircraft Loss

“…For instance, work [12] demonstrates the use of UAV formations to tackle wildfires; it shows that cooperative tracking errors could be bounded even in case of actuator faults. Article [13] investigates UAV formation stability by applying a Lyapunov function, assuming both actuator faults and communication interrupts. Adaptive control enabled the authors to compensate for actuator faults.…”

Fuzzy adaptive observer–based resilient formation control for heterogeneous multiple unmanned aerial vehicles with false data injection attacks and prescribed performance

“…Many important results on formation control for multi-UAV and reliable flight control algorithms have been proposed, such as the Harris hawks optimization (HHO) turned proportional–integral–derivative (PID) pitch angle control (Izci et al, 2020), fixed-time formation control (Shao et al, 2022), discontinuous communication protocol–based formation control (Han et al, 2021), adaptive hierarchical formation control (Rosa et al, 2019), integral sliding mode formation control (Dehghani and Menhaj, 2016), and adaptive differential evolution–based formation control (Zhang et al, 2019), to name just a few. Overall, the schemes of formation control for multi-UAV can be grouped into the distributed schemes (Han et al, 2021; Rosa et al, 2019; Shao et al, 2022) and the centralized schemes (Dehghani and Menhaj, 2016; Zhang et al, 2019). Compared with the centralized scheme, the distributed scheme has more advantages in utilizing communication and computing resources because there is no need for a central process unit.…”

“…Different from the formation control approaches in Shao et al (2022), Han et al (2021), Rosa et al (2019), Dehghani and Menhaj (2016), Zhang et al (2019), Zamanian et al (2022), Ren et al (2021), Liu et al (2020), Wang et al (2021), Gao et al (2021), Zou and Meng (2019), Yan et al (2022), and Chen et al (2022), the transient formation error constraint of each UAV can be guaranteed by a novel PPC method, which satisfies the demands in safe operation. Meanwhile, the requirement for initial states in the traditional PPC method (Ma et al, 2021; Tong et al, 2015; Zhang et al, 2016; Zhao et al, 2018; Zhou et al, 2020; Zhu et al, 2022) can be completely relaxed.…”