Fuzzy Extended State Observer-Based Sliding Mode Control for an Agricultural Unmanned Helicopter

In the context of agricultural unmanned helicopters, the complex wind disturbances over crop fields and structural perturbations due to variations in pesticide container weights present substantial challenges to flight safety. To address these issues, this paper proposes an innovative fuzzy extended state observer-based sliding mode control (FESO-SMC) methodology aimed at enhancing the aircraft’s resilience against such disturbances. Initially, this study adopts a state expansion strategy to integrate both wind and structural disturbances into a comprehensive disturbance model applicable to the agricultural unmanned helicopter. Following this, a sliding mode control law is formulated with consideration for unknown total disturbances, employing specific sliding mode functions alongside exponential reaching laws. An extended state observer is simultaneously implemented within the sliding mode control framework to estimate and mitigate these disturbances, thereby augmenting the disturbance rejection capabilities of the flight control system. Additionally, the integration of fuzzy logic facilitates adaptive parameter adjustment for the extended state observer, leading to more accurate disturbance estimation. Consequently, a trajectory tracking control system tailored specifically for the agricultural unmanned helicopter has been developed, and its performance was evaluated through simulation experiments. The results indicate that, under certain disturbances, the attitude control error of the FESO-SMC controller is reduced to one-fifth that of traditional sliding mode controllers, while position control accuracy is enhanced more than twofold, thus demonstrating that the proposed FESO-SMC controller not only exhibits superior anti-disturbance capability and robustness but also achieves higher tracking accuracy compared to conventional sliding mode controller.