Abdelrahman Abdelgawad

Abdelrahman Abdelgawad

PhD Student at Boston University working on certified neural control and multi-objective reinforcement learning for safety-critical robotic systems.

Accelerating Lyapunov-Stable Neural Control using Fulfillment Priority Logic

Published in American Control Conference (ACC), 2026

We present a two-stage approach for learning stability-certified neural controllers that achieves up to ~95% reduction in training time compared to existing methods. Our method combines monotonic neural Lyapunov functions with Fulfillment Priority Logic (FPL) to efficiently initialize controllers before formal MILP-based verification.

Status: Accepted, January 2026.

Recommended citation: A. Abdelgawad, B. El Mabsout, Z. Wang, R. Mancuso, S. B. Andersson, R. Tron. "Accelerating Lyapunov-Stable Neural Control using Fulfillment Priority Logic." American Control Conference (ACC), 2026.