Modeling and LQR control of insect sized flapping wing robot
Daksh Dhingra, Kadierdan Kaheman, Sawyer B. Fuller
Abstract
Flying insects perform agile maneuvers like backflips, sharp turns, and collision recovery. Replicating these in sub-gram flying insect robots (FIRs) requires fast and responsive control systems. Current FIRs rely on elaborations of proportional-integral-derivative (PID)-type feedback control, requiring painstaking tuning and task-specific adjustments for complex maneuvers. Optimal control offers a solution but has been limited by approximate models or computational demands unsuitable for onboard implementation. Here, we used a more accurate stroke-averaged model of forces and torques, derived from a sensitive two-axis torque sensor, to implement the first demonstration of optimal control on an FIR that is computationally efficient enough to be performed by a microprocessor carried onboard. Applied to the 150 mg UW RoboFly, this enabled stable hovering (RMS error 2.5 cm) and trajectory tracking at speeds up to 25 cm/s using a linear quadratic regulator (LQR). These results were enabled by a more accurate model and laid the groundwork for integrating low-power receding-horizon control to achieve aggressive maneuvers in FIRs.