Suppressing Self-Excitation in Adaptive Sliding Mode Control: Observer-Based Design and Experimental Validation of Flapping-Wing Micro Aerial Vehicle
Heetae Park, Seungkeun Kim, Jinyoung Suk
AI summary
Problem
Unmodeled actuator dynamics and parametric uncertainties often cause undesirable oscillations and instability in flapping-wing MAVs when using traditional adaptive sliding mode control. This work addresses how to maintain robust attitude stabilization without triggering self-excitation from high-frequency discontinuous control inputs.
Approach
The method routes high-frequency discontinuous control signals through an auxiliary proportional-integral observer loop to bypass physical actuators, while using a barrier function-based adaptive gain to modulate control effort and prevent gain overestimation.
Key results
- Observer-based adaptive sliding mode control framework bypasses actuator excitation
- Barrier function-based adaptive gain prevents overestimation and improves efficiency
- Superior attitude tracking and control efficiency versus PD, classical, and super-twisting SMC
- Effective suppression of self-excitation oscillations under simulated external disturbances
Why it matters
This approach enables more reliable and efficient flight for flapping-wing MAVs in dynamic environments, offering a practical control solution for bio-inspired robotics and micro aerial vehicle engineers.
Abstract
This work covers the design of a sliding mode control to stabilize the attitude of a flapping-wing micro aerial ve- hicle. The approach employs an auxiliary observer loop to avoid system excitation from unmodeled actuator dynamics, a common issue in sliding mode control applications. A proportional-integral observer is constituted in the auxiliary loop to minimize inter- actions with the actuator dynamics and to handle parametric uncertainties in the low bandwidth. Then, the observer-based sliding mode control is designed to track the attitude command with the reconstructed state variables from the observer loop. Furthermore, a barrier function-based adaptive gain strategy is utilized to modulate the control input according to the system’s current state, ensuring efficient use of control effort. Flight experiments were conducted with a freely movable dummy mass attached to the bottom of the vehicle, simulating external disturbances. The proposed sliding mode control outperforms proportional-derivative (PD), classical, and super-twisting sliding mode controllers in both tracking performance and control efficiency, while mitigating self-excitation due to discontinuous input.