Learning techniques such as deep reinforcement learning have been increasingly used in
the controller design for autonomous vehicles, eg, lane changing controllers. Although the …

Abstract We present Barrier-based Simplex (Bb-Simplex), a new, provably correct design for
runtime assurance of continuous dynamical systems. Bb-Simplex is centered around the …

In this paper, we present an algorithm for synthesizing certificates for safety of continuous
time dynamical systems, so-called barrier certificates. Unlike the usual approach of using …

This chapter introduces AI‐Grid: Artificial Intelligence (AI) enabled, provably resilient
networked microgrids. We present a programmable platform that integrates reliable AI …

We propose an approach to synthesize Simplex architectures that are provably correct for a
rich class of temporal specifications, and are high-performant by optimizing for the time the …

Recent advances in machine learning technologies and sensing have paved the way for the
belief that safe, accessible, and convenient autonomous vehicles may be realized in the …

Abstract Cyber-Physical Systems (CPSs) are ubiquitous through our interactions with
applications such as smart homes, medical devices, avionics, and automobiles. However …

For a constrained nonlinear control system, an automated supervisor is proposed that
determines switching between a barrier function-certified controller and an uncertified …

Runtime Assurance (RTA) is a design-time architecture for safety-critical systems where an
internal monitor acts upon detecting a violation of a property. The simplex architecture is an …

Abstract We present Barrier-based Simplex (Bb-Simplex), a new, provably correct design for
runtime assurance of continuous and hybrid dynamical systems. Bb-Simplex is centered …