Anti interference and fault tolerant control of UAVs integrating residual based diagnosis disturbance estimation with counter drone strategies

无人机抗干扰和容错控制,融合基于残差的诊断干扰估计和反无人机策略

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Abstract

Unmanned Aerial Vehicles (UAVs) are increasingly deployed in complex, uncertain, and adversarial environments, yet they remain vulnerable to actuator faults, environmental disturbances, and deliberate interferences such as jamming or spoofing. Conventional control approaches typically address these challenges independently, focusing on either fault-tolerant control (FTC), disturbance rejection, or counter-UAV defense. This paper presents an integrated anti-interference and fault-tolerant control framework that unifies three complementary modules: (i) residual-based fault detection and isolation, (ii) adaptive extended state observer (AESO)-based disturbance estimation and compensation, and (iii) counter-UAV evasive maneuver strategies. The framework is formulated using a nonlinear UAV dynamic model and rigorously analyzed under Lyapunov stability theory. Simulation results demonstrate significant performance improvements compared with baseline controllers. The proposed method reduced position and attitude deviations to below 0.05 m and 0.03 deg, respectively, under simultaneous actuator faults and wind disturbances. Fault and disturbance estimation errors remained below 0.05 and 0.03 units, respectively, ensuring timely control reconfiguration. Furthermore, the UAV achieved a 100% success rate in counter-drone evasive maneuvers while maintaining trajectory stability. These results confirm that the integrated design provides high resilience, rapid recovery, and reliable performance in fault-disturbed and adversarial conditions. By bridging FTC, adaptive disturbance rejection, and counter-UAV defense, the proposed framework advances the state of the art in resilient UAV control for civilian and defense applications.

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