Abstract
In this paper, a synthetic jet actuators (SJA)-based nonlinear robust controller is developed, which is capable of completely suppressing limit cycle oscillations (LCO) in UAV systems with parametric uncertainty in the SJA dynamics and unmodeled external disturbances. Specifically, the control law compensates for uncertainty in an input gain matrix, which results from the unknown airflow dynamics generated by the SJA. Challenges in the control design include compensation for input-multiplicative parametric uncertainty in the actuator dynamic model. The result was achieved via innovative algebraic manipulation in the error system development, along with a Lyapunov-based robust control law. A rigorous Lyapunov-based stability analysis is utilized to prove asymptotic LCO suppression, considering a detailed dynamic model of the pitching and plunging dynamics. Numerical simulation results are provided to demonstrate the robustness and practical performance of the proposed control law.
Highlights
There has recently been a surge of interest in the design and application of unmanned aerial vehicles (UAVs)
Suppression of limit cycle oscillations (LCO) is an important concern in UAV tracking control design. This is especially true for applications involving smaller, lightweight UAV systems, where the aircraft wings are more susceptible to LCO
In the following control development and stability analysis, it will be assumed that the matrix B is uncertain, and the robust control law will be designed with a constant feedforward estimate of the uncertain matrix
Summary
There has recently been a surge of interest in the design and application of unmanned aerial vehicles (UAVs). Suppression of limit cycle oscillations (LCO) (or flutter) is an important concern in UAV tracking control design This is especially true for applications involving smaller, lightweight UAV systems, where the aircraft wings are more susceptible to LCO. Developed nonlinear control methods using SJA typically utilize neural networks and/or complex fluid dynamics computations in the feedback loop (e.g., see [9,10,12,13,14,15,16,17,18,19,20,21]) While such approaches have been shown to yield good SJA-based control performance, they can require increased computational resources, which might not be available in small UAV applications. Numerical simulation results are provided to demonstrate the performance of the proposed control law
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