Learning Lyapunov-Stable Polynomial Dynamical Systems through Imitation
We present an approach for learning policies represented by globally stable nonlinear dynamical systems. We model the nonlinear dynamical system as a parametric polynomial and learn the polynomial's coefficients jointly with a learnable Lyapunov candidate to guarantee stability and predictability of the policy.
Oct 12, 2023
