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Spiking Neuromorphic Controller Stabilizes Periodic Orbits in Underactuated Robots: A Greedy Lyapunov-Based Approach

This paper investigates event-driven spiking controllers implemented as spiking neural networks for trajectory tracking in underactuated robots, with the goal of stabilizing a prescribed periodic orbit. The authors reduce orbital stabilization to stabilizing the trivial solution of a periodic linear time-varying system via transverse linearization, and extend a Lyapunov-based greedy design originally developed for LTI systems to this periodic LTV transverse dynamics, thereby constructing a feedback controller. The method's effectiveness is demonstrated on the trajectory stabilization problem for the butterfly robot.

Part of the event: Pulse Neural Controller Stabilizes Periodic Orbits of Underactuated Robots

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