Model identification for a flapping-wing robot based on improved squirrel search algorithm

In this paper, we introduce a novel system identification method for developing a dynamic model of the independently developed flapping-wing robot (FWR). This method emphasizes the significance of the flapping-wing motion by constructing an independent frame for each flapping-wing, thereby enhancing the authenticity of the model's structure. To address the unknown parameters within this model, we propose a parameter identification approach based on the Improved Squirrel Search Algorithm. This approach effectively addresses model uncertainties caused by flapping-wing motion, and experimental comparisons reveal its efficiency in parameter identification. Furthermore, to validate the dynamic model derived from this system identification method, three different maneuvers are selected to test the adaptability of the identified model. The experimental results demonstrate that this method can accurately reflect the flight characteristics of the underactuated FWR. This research provides valuable insights and foundations for future FWR control studies.