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Conjugate Momentum-Based Estimation of External Forces for Bio-Inspired Morphing Wing Flight

Bibek Gupta, Eric Sihite, Alireza Ramezani

Abstract

Dynamic morphing wing flights present significant challenges in accurately estimating external forces due to complex interactions between aerodynamics, rapid wing movements, and external disturbances. Traditional force estimation methods often struggle with unpredictable disturbances like wind gusts or unmodeled impacts that can destabilize flight in real-world scenarios. This paper addresses these challenges by implementing a Conjugate Momentum-based Observer, which effectively estimates and manages unknown external forces acting on the Aerobat, a bio-inspired robotic platform with dynamically morphing wings. Through simulations, the observer demonstrates its capability to accurately detect and quantify external forces, even in the presence of Gaussian noise and abrupt impulse inputs. The results validate the robustness of the method, showing improved stability and control of the Aerobat in dynamic environments. This research contributes to advancements in bio-inspired robotics by enhancing force estimation for flapping-wing systems, with potential applications in autonomous aerial navigation and robust flight control.

Conjugate Momentum-Based Estimation of External Forces for Bio-Inspired Morphing Wing Flight

Abstract

Dynamic morphing wing flights present significant challenges in accurately estimating external forces due to complex interactions between aerodynamics, rapid wing movements, and external disturbances. Traditional force estimation methods often struggle with unpredictable disturbances like wind gusts or unmodeled impacts that can destabilize flight in real-world scenarios. This paper addresses these challenges by implementing a Conjugate Momentum-based Observer, which effectively estimates and manages unknown external forces acting on the Aerobat, a bio-inspired robotic platform with dynamically morphing wings. Through simulations, the observer demonstrates its capability to accurately detect and quantify external forces, even in the presence of Gaussian noise and abrupt impulse inputs. The results validate the robustness of the method, showing improved stability and control of the Aerobat in dynamic environments. This research contributes to advancements in bio-inspired robotics by enhancing force estimation for flapping-wing systems, with potential applications in autonomous aerial navigation and robust flight control.

Paper Structure

This paper contains 9 sections, 16 equations, 8 figures.

Table of Contents

  1. Introduction
  2. Modeling
  3. KS Kinematic Constraints Modeling
  4. Flight Dynamics Modeling
  5. Aerodynamic Modeling
  6. Conjugate Momentum Based Force Estimation
  7. Modeling of Temporal Noise and Step Input in Force Estimation
  8. Results
  9. Conclusion

Figures (8)

  • Figure 1: Shows Aerobat platform sihite_actuation_2023. The platform is designed to study inertial and aerodynamic dynamics' contribution roles in dynamic morphing wing flight.
  • Figure 2: Schematic of the Kinetic Sculpture (KS) mechanism featuring 7 linkages (L1 to L7) and 10 joints (J1 to J10). The KS is uniquely engineered to be driven by a single actuator. This design includes two pivotal angles: $\theta_s$ and $\theta_e$ representing the shoulder and elbow joint angles respectively sihite_actuation_2023.
  • Figure 3: Aerobat with simplified linkages model using five rotating bodies, the linear position ${p}$ represents the center of mass, and ${l}$ represents the length vectors relevant to the Aerobat model conformation.
  • Figure 4: Block diagram of the conjugate momentum observer
  • Figure 5: Shows position of Aerobat in a 3D space over a 2-second interval.
  • ...and 3 more figures